NISTIR 8034

Fingerprint Vendor Technology Evaluation

Craig Watson

Gregory Fiumara

Elham Tabassi

Su Lan Cheng

Patricia Flanagan

Wayne Salamon

http://dx.doi.org/10.6028/NIST.IR.8034
NISTIR 8034

Fingerprint Vendor Technology Evaluation

Craig Watson

Gregory Fiumara

Elham Tabassi

Su Lan Cheng

Patricia Flanagan

Wayne Salamon

Information Access Division

Information Technology Laboratory

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.IR.8034

December 2014

U.S. Department of Commerce

Penny Pritzker, Secretary

National Institute of Standards and Technology

Willie May, Acting Under Secretary of Commerce for Standards and Technology and Acting Director
Fingerprint Vendor Technology Evaluation

Evaluation of Fingerprint Matching Algorithms

NIST Interagency Report 8034

Craig Watson • Gregory Fiumara • Elham Tabassi

Su Lan Cheng • Patricia Flanagan • Wayne Salamon

18 December 2014
iv FPVTE – FINGERPRINT MATCHING

Acknowledgements

. Sponsors: The authors would like to thank the sponsors of this project: the Department of Homeland

Security (DHS) and the Federal Bureau of Investigation (FBI).

. Data Providers: The authors would like to thank all the organizations that have shared biometric data

with NIST for this and other evaluations. This data has proven invaluable for benchmarking and advancement of biometric matching technologies through these evaluations. Data used in FpVTE came

from the FBI, DHS, Los Angeles County Sheriff’s Department (LACNTY), Arizona Department of Public

Safety (AZDPS), and Texas Department of Public Safety (TXDPS).

. Participants: The authors would also like to thank the participants for their time and contribution to

this evaluation. We know that preparing the software for the evaluation is not a trivial task and the

validation process can be stressful when problems occur. Thank you for your time and participation as

this evaluation would not be possible without it.

Disclaimer

Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the

experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials or

equipment identified are necessarily the best available for the purpose.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING v

Contents

Acknowledgements iv

Disclaimer iv

Executive Summary xiii

Caveats xv

Release Notes xvi

1 Introduction 1

2 History and Motivation 3

2.1 NIST Biometric Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.2 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3 Data 5

3.1 Classes of Participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.2 Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3.3 Evaluation Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.4 “Size” of the Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

4 Experiment and Test Protocol 10

4.1 API Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1.1 Feature Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1.2 Finalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1.3 Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.2 Test Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.3 Biometric Evaluation Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.4 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.5 Pre-Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.6 Receiving Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5 Two-Stage Matching 16

5.1 Enrollment Set Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

5.2 Identification — Stage One . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

5.3 Identification — Stage Two . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

6 Metrics 18

6.1 Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

6.2 DET Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

6.3 Failure to Extract or Match a Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

6.4 Computational Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

6.5 Ground Truth Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
vi FPVTE – FINGERPRINT MATCHING

7 Accuracy Results 22

7.1 Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

7.1.1 Single-Index Finger Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

7.1.2 Two-Index Finger Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

7.2 Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

7.3 Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

8 Accuracy/Search Time Tradeoff 41

8.1 Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

8.2 Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

8.3 Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

9 Accuracy Computational Resources Tradeoff 61

9.1 Storage and Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

9.1.1 Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

9.1.2 Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

9.1.3 Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

9.2 Processing Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

10 Ranked Results 78

11 How Many Fingers are Needed 82

12 FpVTE 2003 Comparison 83

13 Lessons Learned for Large-Scale Testing 86

14 Way Forward 88

14.1 Related Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

14.1.1 Forensic Palmprint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

14.1.2 Mobile Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

14.1.3 Cross-Comparison of Modalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

References 89

A Individual Participant FNIR Plots 90

B Combined Class DETs and CMCs 109

C Accuracy Time Tradeoff Detailed Tables with Median Values 114

D Accuracy Time Tradeoff Detailed Tables with Mean Values 128

E Progression for Last Two Submissions 142

F Enrollment Size 153

G Search Template Sizes 160

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING vii

G.1 Mean Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

G.2 Median Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

H Template Creation Times 168

I Ranked Results 178

J Relative Combined Results 188

K Relative Accuracy and Number of Fingers 198

K.1 Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199

K.2 Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

K.3 Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203

K.4 All Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

L Combined Sorted Rankings for a Theoretical Use Case 207

List of Figures

1 NIST Biometric Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Example of Single-Finger Captures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3 Example of an Identification Flat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

4 Examples of Live-Scan and Rescanned Ink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

5 NFIQ Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

6 Number of Submissions Received . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

7 Evaluation Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

9 Example of a Flipped Single-Index Finger Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

8 Example of a DET showing a Spike in FPIR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

10 Example of a Flipped Left Slap Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

11 Example of a Flipped Right Slap Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

12 Rank-sorted FNIR for Class A — Single Index Finger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

13 DET for Class A — Single Index Finger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

14 CMC for Class A — Single Index Finger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

15 Rank-sorted FNIR for Class A — Two Index Fingers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

16 DET for Class A — Two Index Fingers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

17 CMC for Class A — Two Index Fingers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

18 Rank-sorted FNIR for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

19 DET for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

20 CMC for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

21 Rank-sorted FNIR for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

22 DET for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

23 CMC for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

24 FNIR and Search Time Scatter Plot — Class A — Left Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . . 43

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
viii FPVTE – FINGERPRINT MATCHING

25 FNIR and Search Time Scatter Plot — Class A — Left Index — Greater Than or Equal To 20-Second Searches . . . . . . . 43

26 FNIR and Search Time Scatter Plot — Class A — Right Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . 44

27 FNIR and Search Time Scatter Plot — Class A — Right Index — Greater Than or Equal To 20-Second Searches . . . . . . 44

28 FNIR and Search Time Scatter Plot — Class A — Left and Right Index — Less Than 20-Second Searches . . . . . . . . . . 45

29 FNIR and Search Time Scatter Plot — Class A — Left and Right Index — Greater Than or Equal To 20-Second Searches . 45

30 Submission Round Progression — Class A — Left Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . . . . 46

31 Submission Round Progression — Class A — Left Index — Greater Than or Equal To 20-Second Searches . . . . . . . . . 46

32 Submission Round Progression — Class A — Right Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . . . 47

33 Submission Round Progression — Class A — Right Index — Greater Than or Equal To 20-Second Searches . . . . . . . . 47

34 Submission Round Progression — Class A — Left and Right Index — Less Than 20-Second Searches . . . . . . . . . . . . 48

35 Submission Round Progression — Class A — Left and Right Index — Greater Than or Equal To 20-Second Searches . . . 48

36 FNIR and Search Time Scatter Plot — Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

37 FNIR and Search Time Scatter Plot — Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

38 FNIR and Search Time Scatter Plot — Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

39 FNIR and Search Time Scatter Plot — Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

40 Submission Round Progression — Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

41 Submission Round Progression — Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

42 Submission Round Progression — Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

43 Submission Round Progression — Class B — IDFlat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

44 FNIR and Search Time Scatter Plot — Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

45 Submission Round Progression — Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

46 FNIR and RAM Used for Enrollment Set Tradeoff Scatter Plot for Class A — Left Index . . . . . . . . . . . . . . . . . . . 62

47 FNIR and RAM Used for Enrollment Set Tradeoff Scatter Plot for Class A — Right Index . . . . . . . . . . . . . . . . . . . 62

48 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class A — Left Index . . . . . . . . . . . . . . . . . . . . 63

49 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class A — Right Index . . . . . . . . . . . . . . . . . . . 63

50 FNIR and RAM Used for Enrollment Set Scatter Plot for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . 64

51 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class A — Left and Right Index . . . . . . . . . . . . . . 64

52 Enrollment Size in RAM Compared to On Disk for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . 65

53 Enrollment Size and Search Template Size in RAM Compared to On Disk for Class A — Left and Right Index . . . . . . . 65

54 FNIR and RAM Used for Enrollment Set for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

55 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class B — Identification Flats . . . . . . . . . . . . . . . 67

56 Enrollment Size in RAM Compared to On Disk for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . 68

57 Search Template Size in RAM Compared to On Disk for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . 68

58 FNIR and RAM Used for Enrollment Set Tradeoff Scatter Plot for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . 70

59 FNIR and RAM Used for Enrollment Set Tradeoff Scatter Plot for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . 70

60 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . 71

61 FNIR and Search Template Size in RAM Tradeoff Scatter Plot for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . 71

62 Enrollment Size and Search Template Size in RAM Compared to On Disk for Class C — Plain Impression . . . . . . . . . 72

63 Enrollment Size and Search Template Size in RAM Compared to On Disk for Class C — Plain Impression . . . . . . . . . 72

64 Enrollment Size and Search Template Size in RAM Compared to On Disk for Class C — Rolled Impression . . . . . . . . 73

65 Enrollment Size and Search Template Size in RAM Compared to On Disk for Class C — Rolled Impression . . . . . . . . 73

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING ix

66 FNIR and Template Creation Time Tradeoff Scatter Plot for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . 75

67 FNIR and Template Creation Time Tradeoff Scatter Plot for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . 75

68 FNIR and Template Creation Time Tradeoff Scatter Plot for Class A — Left and Right Index . . . . . . . . . . . . . . . . . 76

69 FNIR and Template Creation Time Tradeoff Scatter Plot for Class B — Identification Flats . . . . . . . . . . . . . . . . . . 76

70 FNIR and Template Creation Time Tradeoff Scatter Plot for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . 77

71 FNIR and Template Creation Time Tradeoff Scatter Plot for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . 77

72 Rank-sorted FNIR for All Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

73 FpVTE 2003 SST Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

74 FpVTE 2003 MST Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

75 FpVTE 2003 LST Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

76 FpVTE 2003 LST Number of Fingers Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

77 DET for Participant C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

78 DET for Participant D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

79 DET for Participant E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

80 DET for Participant F . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

81 DET for Participant G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

82 DET for Participant H . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

83 DET for Participant I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

84 DET for Participant J . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

85 DET for Participant K . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

86 DET for Participant L . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

87 DET for Participant M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

88 DET for Participant O . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

89 DET for Participant P . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

90 DET for Participant Q . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

91 DET for Participant S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

92 DET for Participant T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

93 DET for Participant U . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

94 DET for Participant V . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

95 DET for All Participants in All Classes — First Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

96 DET for All Participants in All Classes — Second Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

97 CMC for All Participants in All Classes — First Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

98 CMC for All Participants in All Classes — Second Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

99 Relative Combined Results — Left Index — Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189

100 Relative Combined Results — Right Index — Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190

101 Relative Combined Results — Left and Right Index — Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191

102 Relative Combined Results — Left Slap — Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

103 Relative Combined Results — Right Slap — Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

104 Relative Combined Results — Left and Right Slap — Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194

105 Relative Combined Results — Identification Flats — Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

106 Relative Combined Results — Ten-Finger Plain-to-Plain — Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
x FPVTE – FINGERPRINT MATCHING

107 Relative Combined Results — Ten-Finger Rolled-to-Rolled — Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

108 Relative Accuracy — Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

109 Relative Accuracy — Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202

110 Relative Accuracy — Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204

111 Relative Accuracy — All Classes (Select Fingers) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

List of Tables

1 List of Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3 Evaluation Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

4 Search and Enrollment Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

5 Number of Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

6 Finger Position Swapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

7 FNIR @ FPIR = 10−3 — Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

8 FNIR @ FPIR = 10−3 — Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

9 FNIR @ FPIR = 10−3 — Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

10 FNIR @ FPIR = 10−3 — Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

11 FNIR @ FPIR = 10−3 — Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

12 FNIR @ FPIR = 10−3 — Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

13 FNIR @ FPIR = 10−3 — Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

14 FNIR @ FPIR = 10−3 — Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

15 FNIR @ FPIR = 10−3 — Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

16 FNIR @ FPIR = 10−3 — Class C — Ten-Finger Plain-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

17 Median Identification Times for Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

18 Median Identification Times for Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

19 Median Identification Times for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

20 Median Identification Times for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

21 Ranked Results for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

22 Ranked Results for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

23 Ranked Results for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

24 Median Identification Time Results for Class A — Left Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . 115

25 Median Identification Time Results for Class A — Left Index — Greater Than or Equal To 20-Second Searches . . . . . . 116

26 Median Identification Time Results for Class A — Right Index — Less Than 20-Second Searches . . . . . . . . . . . . . . 117

27 Median Identification Time Results for Class A — Right Index — Greater Than or Equal To 20-Second Searches . . . . . . 118

28 Median Identification Time Results for Class A — Left and Right Index — Less Than 20-Second Searches . . . . . . . . . 119

29 Median Identification Time Results for Class A — Left and Right Index — Greater Than or Equal To 20-Second Searches 120

30 Median Identification Time Results for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

31 Median Identification Time Results for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

32 Median Identification Time Results for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

33 Median Identification Time Results for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING xi

34 Median Identification Time Results for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . 125

35 Median Identification Time Results for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . 126

36 Median Identification Time Results for Class C — Ten-Finger Plain-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . 127

37 Mean Identification Time Results for Class A — Left Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . . 129

38 Mean Identification Time Results for Class A — Left Index — Greater Than or Equal To 20-Second Searches . . . . . . . . 130

39 Mean Identification Time Results for Class A — Right Index — Less Than 20-Second Searches . . . . . . . . . . . . . . . 131

40 Mean Identification Time Results for Class A — Right Index — Greater Than or Equal To 20-Second Searches . . . . . . . 132

41 Mean Identification Time Results for Class A — Left and Right Index — Less Than 20-Second Searches . . . . . . . . . . 133

42 Mean Identification Time Results for Class A — Left and Right Index — Greater Than or Equal To 20-Second Searches . . 134

43 Mean Identification Time Results for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

44 Mean Identification Time Results for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

45 Mean Identification Time Results for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

46 Mean Identification Time Results for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138

47 Mean Identification Time Results for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

48 Mean Identification Time Results for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . 140

49 Mean Identification Time Results for Class C — Ten-Finger Plain-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . 141

50 Progression of Identification Timing and Accuracy for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . 143

51 Progression of Identification Timing and Accuracy for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . 144

52 Progression of Identification Timing and Accuracy for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . 145

53 Progression of Identification Timing and Accuracy for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

54 Progression of Identification Timing and Accuracy for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . 147

55 Progression of Identification Timing and Accuracy for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . 148

56 Progression of Identification Timing and Accuracy for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . 149

57 Progression of Identification Timing and Accuracy for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . 150

58 Progression of Identification Timing and Accuracy for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . 151

59 Progression of Identification Timing and Accuracy for Class C — Ten-Finger Plain-to-Rolled . . . . . . . . . . . . . . . . 152

60 Storage and RAM Requirements for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

61 Storage and RAM Requirements for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

62 Storage and RAM Requirements for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

63 Storage and RAM Requirements for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

64 Storage and RAM Requirements for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158

65 Storage and RAM Requirements for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . 159

66 Mean Search Template Sizes for Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

67 Mean Search Template Sizes for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

68 Mean Search Template Sizes for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

69 Median Search Template Sizes for Class A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

70 Median Search Template Sizes for Class B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166

71 Median Search Template Sizes for Class C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167

72 Enrollment Time Results for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

73 Enrollment Time Results for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170

74 Enrollment Time Results for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
xii FPVTE – FINGERPRINT MATCHING

75 Enrollment Time Results for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172

76 Enrollment Time Results for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173

77 Enrollment Time Results for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174

78 Enrollment Time Results for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

79 Enrollment Time Results for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

80 Enrollment Time Results for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

81 Ranked Results for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

82 Ranked Results for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

83 Ranked Results for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

84 Ranked Results for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

85 Ranked Results for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

86 Ranked Results for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

87 Ranked Results for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

88 Ranked Results for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

89 Ranked Results for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187

90 Operational Ranking for Class A — Left Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209

91 Operational Ranking for Class A — Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

92 Operational Ranking for Class A — Left and Right Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

93 Operational Ranking for Class B — Left Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

94 Operational Ranking for Class B — Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

95 Operational Ranking for Class B — Left and Right Slap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214

96 Operational Ranking for Class B — Identification Flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215

97 Operational Ranking for Class C — Ten-Finger Plain-to-Plain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

98 Operational Ranking for Class C — Ten-Finger Rolled-to-Rolled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING xiii

Executive Summary

FpVTE was conducted primarily to assess the current capabilities of fingerprint matching algorithms using operational

datasets containing several million subjects. There were three classes of participation that examined one-to-many identification using various finger combinations from single finger up to ten fingers. Class A used single-index finger capture

data and evaluated single index finger (right or left) and two index finger (right and left) identification. Class B used

identification flat (IDFlat) captures (4-4-2; left slap, right slap, and two thumbs simultaneously) and evaluated ten-finger,

eight-finger (right and left slap), and four-finger (right or left slap) identification. Class C used rolled and plain impression

(4-4-1-1; left slap, right slap, left thumb, and right thumb) captures and evaluated ten-finger rolled-to-rolled, ten-finger

plain-to-plain, and ten-finger plain-to-rolled identification. Enrollment sets used for one-to-many identification varied in

size from 5 000 up to 5 000 000 enrolled subjects. Any segmentation of four-finger slap images or two-thumb captures was

performed by the submitted software. All data used was sequestered operational data that was not shared with any of the

participants.

The evaluation allowed each participant to make two submissions per class (A, B, and C) of participation over three

rounds. After each of the first two rounds of submissions, feedback was provided to the participants and they were

allowed to evaluate their performance, make adjustments to their submissions, and resubmit for the next round. The

results of the third and final round of submissions are reported in this document.

The evaluation was conducted at the National Institute of Standards and Technology (NIST) using commodity NISTowned hardware. Participant submissions were compliant to the testing Application Programming Interface (API), which

were linked to a NIST-developed test driver and run by NIST employees. All submissions went through validation testing

to ensure that results generated on NIST’s hardware matched results participants generated on their own hardware.

This was the first large-scale one-to-many fingerprint evaluation since FpVTE 2003. In 2003, participants brought their

own hardware to NIST to process the evaluation data. The datasets in 2003 had approximately 25 000 subjects and required millions of single subject-to-subject matches. The current FpVTE used a testing model closer to real one-to-many

identification systems by allowing the submitted software to control how it does the one-to-many search and return a

candidate list of potential matches. The number of subjects used was also significantly higher, as the current FpVTE had

≈ 10 million subjects in the testing datasets.

The results in this report are based on 30 000 (10 000 mates and 20 000 nonmates) search subjects. There will be an additional report with results (lower errors rates) using 350 000 (50 000 mates and 300 000 nonmates) search subjects.

In addition to measuring current performance capabilities of one-to-many identification algorithms, FpVTE was conducted

to:

. study open-set identification versus enrolled sample sizes extending into the multiple millions;

. provide a testing framework and API for enrollment sizes that must be spread across the memory of multiple compute nodes;

. evaluate on operational datasets containing newer data from live-scan ten-finger “identification flat” capture systems, other live-scan capture devices (e.g., single-finger and multi-finger), and historically significant scanned inked

fingerprints;

. analyze one-to-many identification accuracy, speed, template size, number of fingers, enrollment set sizes, and computational resources;

. create a fingerprint testing data repository with a vast majority of data errors corrected.

FpVTE was not intended to:

. measure performance of an operational Automated Fingerprint Identification System (AFIS);

. evaluate scanners or acquisition devices;

. evaluate latent fingerprint or mobile-captured data.

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xiv FPVTE – FINGERPRINT MATCHING

Key results from FpVTE were:

. Fingerprint Identification Accuracy: The most accurate fingerprint identification submissions achieved false negative identification rates (FNIR, or “miss rates”) of 1.9% for single index fingers, 0.27% for two index fingers, 0.45%

for four-finger identification flats (IDFlats), 0.15% for eight-finger IDFlats, 0.09% for ten-finger IDFlats, 0.1% for tenfinger rolled-to-rolled, 0.13% for ten-finger plain-to-plain, and 0.11% for ten-finger plain-to-rolled. These numbers

are reported at a false positive identification rate (FPIR) of 10−3. 30 000 search subjects were used for these results

(10 000 mates and 20 000 nonmates). The number of enrolled subjects used for single index fingers was 100 000, 1.6

million for two index fingers, 3 million for IDFlats, and 5 million for ten finger plains and rolled. A larger search set

(50 000 mates and 300 000 nonmates) is being completed so that an even smaller FPIR can be reported. Those results,

when available, will be included in an additional report. Section 7.

. Accuracy versus Speed: The fastest submissions were not the most accurate. The most accurate submissions showed

the ability to decrease search times with minimal loss in accuracy. The format of this evaluation may not have fully

explored the lower limit of search speed with minimal loss in accuracy. Section 8 and Appendix E.

. Number of Fingers: Not surprisingly, using more fingers improved accuracy. In fact, the most accurate results were

achieved with ten fingers, searching against the largest enrollment sets of 3 and 5 million subjects. An interesting

result that needs further study and analysis is that two-index finger accuracy was better than four-finger IDFlats.

Based on some analysis of missed mates, it appears image quality may have played some roll in this result. Section 11.

. Computation Resources: The most accurate submissions were able to achieve their results with similar Random

Access Memory (RAM) usage to other submissions. These same accurate submissions typically took longer to enroll

(i.e., extract features) the fingerprint images used in the evaluation. Section 9.

. Candidate Lists: For most top performers, a majority of the time, the mate appeared within the top three candidates

of the candidate list or did not appear at all. Section 7.

. Ranked Results: Results that group FNIR, enrollment time, search time, and RAM usage all in a single table are

shown in Section 10 and Appendix I. The tables are rank-sorted on FNIR, but include ranks in all the other categories

for cross-category comparison.

. Number of Subjects in Enrollment Set: Results for different enrollment set population sizes will not be available

until the larger search sets are complete, but the initial results across classes of participation showed that eight- and

ten-finger accuracy was superior versus larger enrollment sets. In fact, the most accurate identification results were

always achieved with the ten-finger search sets. Section 7.

. Data Type: There were three classes of participation in which data from single fingers, IDFlats, and “legacy” tenfinger rolled and plain impression data types were evaluated. Results of IDFlats and ten-finger rolled and plain

showed little variation in the accuracy of the top-performing submissions. This means the best performers could

tune their submissions to accurately match all the data types evaluated. Section 10.

. Accuracy Gap: The “gap” between the most accurate submissions and the “next tier” appears to be much closer

than in FpVTE 2003. Sections 10 and 12.

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FPVTE – FINGERPRINT MATCHING xv

Caveats

1. Specific nature of the biometric data: The absolute error rates quoted here were measured over a very large fixed

corpus of operational fingerprint images. The error rates measured here are realistic if the submissions are applied

to this kind of data. However, in other applications, the applicability of the results may differ due to a number of

factors legitimately not reflected in the FpVTE experimental design. Among these are:

. how much slap fingerprint segmentation errors contribute to core matching accuracy;

. algorithmic limitations caused by the FpVTE API;

. unknown bugs in the submission;

. image quality from using a different data source.

2. Not an Automated Fingerprint Identification System (AFIS) test: While this evaluation is intended to measure the

core capabilities of matching algorithms in a large one-to-many scenario, it is not intended to be a full assessment of

an operational AFIS.

3. Timing of the submissions: While every attempt was made to perform timing on the exact same hardware with the

exact same conditions, it is possible that certain functions of the operating system could have had an unintended

negative effect on timing results. The timing operations reported for each submission submitted were performed in

the exact same manner. Generous “cutoff” times were employed to prevent wasting compute cycles on submissions

whose API functions never returned a value.

4. Aggregate finger positions: When reporting estimated template RAM usage statistics, participants were permitted

to return an aggregate template size when the input image contained more than one finger (e.g., “slaps”). Any

statistics over these types of images were reported as-is and the values were not divided by the number of fingers

expected for the capture type. While these participants are not denoted in the report, the actual RAM usage may be

a better statistic for comparison.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

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xvi FPVTE – FINGERPRINT MATCHING

Release Notes

All FpVTE related reports, drafts, announcements, and news items may be found on the website

http://fingerprint.nist.gov.

. Application Program Interface and Test Plan: The FpVTE API [15] contains additional details about creating a

submission compatible with the FpVTE test driver. All submissions tested in FpVTE from 2012-2014 were fully

compatible with the FpVTE API and linked without modification to the FpVTE test driver.

. Appendices: Appendix A has full-scale plots for individual participant results that some may prefer to the grouped

plots in the main body of the report. Appendices B through L have complete sets of tables for various analyses to

help reduce the number of tables in the main body of the report.

. Submission identifiers: Throughout this report, submissions are identified by letter code. For reference, the letters

are associated with the providers’ names in a running footnote.

. Typesetting and Graphics: Virtually all of the content in this report was produced automatically. This involved the

use of scripting tools to generate LATEX content and 
R graphs directly from the FpVTE test driver’s output. Other

graphics were produced with TikZ. Use of these technologies improved timeliness, flexibility, maintainability, and

reduced transcription errors.

. Evaluation Data Ground Truth: Unknown mates within and across datasets create a significant problem and time

delay for large one-to-many data testing.

. Contact: Correspondence regarding this report should be directed to FPVTE at NIST dot GOV.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 1

1 Introduction

In 2012, NIST launched a new Fingerprint Vendor Technology Evaluation (FpVTE) with two main goals. The first goal

was to assess the current capabilities of matching algorithms using operational datasets with several million subjects. The

second goal was to evaluate different operational considerations that could impact matching accuracy. These considerations included number of fingers used, data types (live-scan, single-finger capture, slap capture requiring segmentation,

and rolled), number of enrolled subjects, and matching speeds.

Evaluating biometric capabilities is an important task, particularly for fingerprint identification, given its widespread

applications. Large-scale evaluations of core accuracy and functionality of biometric recognition algorithms using operational data will not only reveal the capabilities of the current state of the art but can also identify the limitations and

gaps of the current algorithms. The former sets realistic operational expectations and the latter directs future research to

improve and enhance current technologies.

FpVTE was conducted by NIST and sponsored by the Department of Homeland Security (DHS) and the Federal Bureau

of Investigation (FBI). All work was performed at the NIST Gaithersburg facility using hardware owned by NIST. FpVTE

includes three rounds of submissions, with participants making algorithm adjustments based on performance reports after

the first two submissions. Participant submissions were required to conform to the test plan API [15].

The evaluation had three classes of participation. Class A used single-index finger capture data and evaluated single

index fingers searched against 5 000 up to 100 000 enrolled subjects (“single-finger identification”), and two index fingers

searched against 10 000 up to 1 600 000 enrolled subjects (“two-finger identification”). Class B used IDFlat captures (4-

4-2) and evaluated ten-finger, eight-finger (right and left slap), and four-finger (right or left slap) identification searched

against 500 000 up to 3 000 000 enrolled subjects. Class C used rolled and plain impression (4-4-1-1) captures and evaluated

ten-finger rolled impression, ten-finger plain impression, and ten-finger plain impression matched to rolled impression

identification searched against 500 000 up to 5 000 000 enrolled subjects. Any segmentation of four-finger slap images or

two-thumb captures was performed by the submission.

Biometric identification is defined as, “[the] process of searching against a biometric enrollment database to find and return

the biometric reference identifier(s) attributable to a single individual” [7]. Biometric identification is broadly categorized

into closed-set and open-set identification.

Closed-set identification refers to cases where all searches have a corresponding enrolled mate in the biometric enrollment

database. An example of a closed-set identification application is a cruise ship on which all passengers are enrolled. The

outcome of a closed-set identification subsystem is a candidate list that contains the identity of one or more enrolled

individuals whose enrolled samples are most similar to the search (query) sample. Ideally, the correct mate appears in

the first rank. As such, the primary accuracy metric for closed-set identification is hit rate (or its complement, miss rate =

1.0 − hit rate), which is the fraction of times the system returns the correct identity within the specified top ranks.

In open-set identification, not all searches have a corresponding enrolled mate in the biometric enrollment database [3].

The expected outcome of an open-set identification subsystem is a candidate list of L closest (or most similar) enrolled

identities when the search sample is from an enrolled individual, or an indication that the search sample is from an

individual not in the biometric enrollment database. Therefore, primary accuracy metrics for an open-set identification

are false positive identification (false alarm or Type I error) rate and false negative identification (miss or Type II error)

rate. These metrics are described in Section 6.

Closed-set identification applications are very limited because in the majority of real-world identification applications,

not all individuals are or can be enrolled. Most real-world biometric identification applications, such as searches against a

watch-list or searches for first-time arrestees, are open-set identification. For that reason, FpVTE only evaluated open-set

identification algorithms.

This document reviews metrics for evaluating the performance of open-set identification algorithms and reports performance for submissions from 18 participants. Three participated in Class A only and the other 15 submitted for all three

classes. Four participants withdrew before making a submission for testing. Table 1 shows the list of participants and in

which classes they made submissions for evaluation. These participants are referenced at the bottom of every page with

their assigned identification letter.

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I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

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2 FPVTE – FINGERPRINT MATCHING

ID Name Participation Class

C afis team A, B, C

D 3M Cogent A, B, C

E Neurotechnology A, B, C

F Papillon A, B, C

G Dermalog A, B, C

H Hisign Bio-Info Institute A, B, C

I NEC A, B, C

J Sonda A, B, C

K Tiger IT A

L Innovatrics A, B, C

M SPEX A, B, C

O ID Solutions A, B, C

P id3 A

Q Morpho A, B, C

S Decatur Industries A, B, C

T BIO-key A

U Aware A, B, C

V AA Technology A, B, C

Table 1: Participant IDs, names, and classes of submission for evaluation.

Section 2 has some history on fingerprint evaluations performed at NIST. Section 3 describes the data used in FpVTE.

Section 4 describes the protocol used for submission acceptance and testing. Section 5 gives details on the two-stage

matching approach used in FpVTE. Sections 6 through 11 talk about the metrics used to measure accuracy and report the

results from testing. While recognition error rates are important and widely reported, computational resources required

by algorithms are a significant aspect of performance, especially for large-scale operations. To that end, we report the

computation time, storage requirements, and their accuracy tradeoffs for each of the submissions. Finally, Section 12

examines some FpVTE 2003 results, then Section 13 and Section 14 talk about some lessons learned and future plans.

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I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

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FPVTE – FINGERPRINT MATCHING 3

2 History and Motivation

2.1 NIST Biometric Evaluations

The first one-to-many fingerprint evaluation conducted at NIST was FpVTE 2003. This evaluation required that participants bring their own hardware and software to NIST for the evaluation. NIST supplied the data and retained all

matching results for final analysis. FpVTE 2003 had three classes of participation: Small-Scale, Medium-Scale, and LargeScale. Small-Scale testing used 1 000 single-finger capture images resulting in 1 million subject-to-subject comparisons.

Medium-Scale testing used 10 000 single-finger captures resulting in 100 million comparisons. Large-Scale testing used

25 000 subjects and various combinations of fingers resulting in 1.044 billion comparisons. The evaluation had 18 participants that submitted 34 systems for testing.

NIST has conducted several fingerprint-related evaluations in the last decade (Figure 1). The first fingerprint evaluation

was called Proprietary Fingerprint Template 2003 (PFT 2003). PFT 2003 was a one-to-one matching evaluation that looked

at the core matching capabilities of fingerprint matching software. It did not evaluate one-to-many capabilities. In 2010,

NIST changed the name of PFT 2003 to PFTII, utilizing newer, larger datasets and reporting information on timing and

template sizes, in addition to accuracy.

Minutiae Exchange (MINEX), also a one-to-one matching evaluation, began in 2005. MINEX was started to support testing

of fingerprint matching technologies using INCITS 378 standard interoperable templates [6]. About a year later, Ongoing

MINEX was created to support Personal Identity Verification (PIV) by establishing guidelines and measuring accuracy for

interoperable template encoders and matchers.

In addition to fingerprint-related evaluations, NIST has performed evaluations for other biometrics such as face and iris.

Additional information and links for all the NIST biometric related evaluations can be found on the NIST biometric evaluations website [5].

FRVT

2002

2003

FpVTE

PFT

SlapSeg

2004

2005

MINEX

FRGC

ICE

FRVT

Biometric

Usability

ICE

2006

2007

ELFT

MINEX II

MBGC

IREX I

2008

2009

SlapSeg II

ELFT

MBE

IQCE

MBE

PFTII

2010

2011

IREX III

NFIQ2

FpVTE

FRVT

IREX IV

2012

2013

FIVE

Tatt-C

2014

Figure 1: NIST biometric evaluations.

2.2 Purpose

One of the main purposes of this FpVTE evaluation was to provide a refresh on the testing performed in 2003 and allow

an opportunity for participation by organizations that missed the previous evaluation. There had been many inquiries in

the past several years on when NIST would perform a similar evaluation. Additionally, the dataset size for FpVTE 2003

was around 25 000 total subjects. The current FpVTE testing used enrollment sets ranging from 10 000 subjects to 5 million

subjects.

NIST has already conducted one-to-many biometric evaluations with enrollment set sizes over 1 million subjects for other

modalities (e.g., Face Recognition Vendor Test (FRVT)/Multiple Biometric Evaluation (MBE) for face and Iris Exchange

Evaluation (IREX III) for iris), in which the sizes of the enrollment templates allowed the entire enrollment set to fit into

the RAM of a single compute node. FpVTE was the first biometric evaluation at NIST that added the ability to partition

the enrollment set across multiple compute nodes, expanding the possibilities in size and breadth of enrollment sets. In

addition to broadening the enrollment set, FpVTE strived to:

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

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4 FPVTE – FINGERPRINT MATCHING

. assess the current performance of one-to-many fingerprint matching software using operational fingerprint data;

. provide a testing framework and API for enrollment sizes that must be spread across the memory of multiple compute nodes;

. support US Government and other sponsors in setting operational thresholds;

. evaluate on operational datasets containing newer data from live-scan ten-finger IDFlat capture systems, other livescan capture devices (e.g., single-finger and multi-finger), and historically significant scanned inked fingerprints;

. analyze one-to-many identification accuracy versus, speed, template size, number of fingers, enrollment set sizes,

and computational resources.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 5

3 Data

3.1 Classes of Participation

FpVTE was separated into three classes of participation: A, B, and C. All participants were required to make a Class A

submission. Along with the Class A submission, a participant could additionally participate in Class B, or both Class B

and Class C. These were the only three participation combinations available.

Images were captured via live-scan sensor and rescanned ink. A live-scan sensor refers to the type of sensor that digitally

records the friction ridges of a finger through techniques such as electrical or optical sensing. Scanned ink is the process of

creating a digital image by using an image scanner to optically capture from paper images of friction ridges created by a

finger covered with ink.

Class A consisted of live-scan single-finger captures of the left and right index fingers (Figure 2).

Figure 2: Example of single-finger captures of left and right index fingers.

Class B consisted of live-scan IDFlats, which captured left and right four-finger slaps and simultaneous left and right

thumbs, known as “4-4-2” (Figure 3).

Figure 3: Example of an identification flat (4-4-2) capture of a left and right slap and left and right thumbs.

Class C consisted of the rolled and plain impressions from a more traditional 14 print card/record and was a mix of

live-scan and rescanned ink (Figure 4).

Figure 4: Example of live-scan and rescanned ink 14 print card/record that include rolled and plain impressions.

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I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
6 FPVTE – FINGERPRINT MATCHING

3.2 Datasets

The evaluation datasets used in FpVTE were from anonymized operational datasets and made available to NIST for fingerprint evaluations. The datasets are for government use only and will not be released to the public. The datasets will,

to the extent permitted by law, be protected under the Freedom of Information Act (5 U.S.C. § 522) and the Privacy Act (5

U.S.C. § 522a) as applicable.

The datasets were comprised of several fingerprint impression types, including rolled, multi-finger plains, and singlefinger plains. Rolled images were all individual captures that attempted to record the full width of the fingerprint by

rolling from side-to-side during capture. Multi-finger plains captured the four right and four left fingers at the same time.

For identification flats, the two thumbs were captured at the same time. Single-finger plains were individual captures of

the right and left index fingers on a single-finger capture device.

Many of the datasets were larger samples of data used in previous NIST evaluations, such as PFT, MINEX, NIST Fingerprint Image Quality (NFIQ), and FpVTE 2003. The single-finger capture and identification flat fingerprint images were

provided by DHS. The ten-finger rolled and slap fingerprint images included data from the FBI, DHS, Los Angeles County

Sheriff’s Department (LACNTY), Arizona Department of Public Safety (AZDPS), and Texas Department of Public Safety

(TXDPS). Table 2 shows the source of data for each class in the evaluation.

Class Dataset Enroll Mate Enroll Nonmate Search Mate Search Nonmate

A

VISIT-I/POEBVA 25% 5% 25% 25%

DHS2 25% 5% 25% 25%

VISIT-II 50% 90% 50% 50%

B

VISIT-II 96% 85% 96% 62.5%

PDR_IDF 4% 15% 4% 37.5%

C

AZDPS 33.3% 4% 33.3% 18.75%

INSBEN 0% 11.5% 0% 12.5%

LACNTY 33.3% 30% 33.3% 18.75%

TXDPS 0% 11.5% 0% 12.5%

PDR-Roll 33.3% 43% 33.3% 37.5%

Table 2: Percentage of data used from each source.

All images in the datasets were 8-bit grayscale. Images were previously compressed using Wavelet Scalar Quantization

(WSQ) compression [2], but were passed to the submitted software as reconstructed raw pixel images, decompressed using

libwsq from NIST’s NIST Biometric Image Software (NBIS) distribution [14]. All images were scanned at 500 pixels per

inch. The dimensions of the images varied, but were provided as input information to the participant’s submission. The

distribution of NIST Fingerprint Image Quality (NFIQ) algorithm [12, 13] values for the evaluation datasets is shown in

Figure 5. NIST Fingerprint Segmentation algorithm (NFSEG) was used to segment slap impression images into individual

fingers before computing NFIQ values.

Multiple-finger plain captures were not segmented. Submissions were required to perform segmentation of fingerprints,

if necessary. Subjects with missing fingers were not removed from the dataset.

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I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 7

Class Fingers Type 1 2 3 4 5

A

L/R Index Enroll 42.8% 32.5% 20.2% 2.2% 2.3%

L/R Index Search 39.5% 32.9% 20.7% 2.2% 4.7%

B

Left Slap Search 44.9% 26.8% 16.0% 6.9% 5.4%

Right Slap Search 50.2% 24.4% 13.0% 5.8% 6.6%

L/R Slap Search 47.6% 25.6% 14.5% 6.3% 6.0%

IDFlats Search 48.3% 25.7% 14.2% 6.4% 5.4%

C

Ten Plain Search 47.8% 26.6% 16.2% 5.5% 3.9%

Ten Rolled Enroll 34.2% 19.5% 25.0% 8.6% 12.7%

Ten Rolled Search 35.4% 21.3% 23.0% 9.1% 11.2%

0%

25%

50%

75%

100%

L/R Index Left Slap Right Slap L/R Slap ID Flats Ten Plain Ten Rolled

Finger

NFIQ 1 2 3 4 5

Figure 5: NFIQ distribution for datasets, after segmentation, where 1 is highest quality and 5 is lowest quality.

3.3 Evaluation Scenarios

Class Scenario

A

S1 x E1

S2 x E2

S3 x E3

B

S4 x E4

S5 x E4

S6 x E4

S7 x E4

C

S8 x E5

S9 x E5

S9 x E6

Table 3: Evaluation scenarios.

Refer to Table 4 for descriptions

of the search and enrollment set

codes.

The three classes of participation had various data type and fingerprint combinations

that could be evaluated as summarized in autoreftab:data-scenarios. The contents of

Table 4 shows details of the search and enrollment sets used during the evaluation for

each class of participation. The final column of Table 4 shows the various sizes of the

datasets that were tested. The subjects reserved for the search sets contained 200 000

with a known mate and 400 000 with no mate in the enrollment set. This report is based

on a random sample of 10 000 mated and 20 000 nonmated searches from the full search

set.

Table 3 shows the various combinations in which the search sets were searched against

the enrollment sets listed in Table 4. Those combinations are also described for each

class as follows.

. Class A — Index Fingers

– One plain index finger searched against an enrollment set of one plain index

fingers. The plain images were from single-finger captures of left and right

index fingers.

– Two plain index fingers searched against an enrollment set of two plain index

fingers. The plain images were from single-finger captures of left and right index fingers.

. Class B — Identification Flats

– Four-, eight-, and ten-finger identification flats (4-4-2, left/right four-finger plain impressions, and a two-thumb

plain impression) searched against an enrollment set of ten-finger identification flats. Any segmentation was

performed by the submission.

. Class C — Ten-Finger Rolled/Slap

– Ten-finger rolled impressions searched against an enrollment set of ten-finger rolled impressions.

– Ten-finger plain impressions searched against an enrollment set of ten-finger plain impressions. Plain impression images were 4-4-1-1 (left/right four-finger plain impression and left/right single-thumb plain impressions). Any segmentation was performed by the submission.

– Ten-finger plain impressions searched against an enrollment set of ten-finger rolled impressions. Plain impression images were 4-4-1-1 (left/right four-finger plain impressions and left/right single-thumb plain impressions). Any segmentation was performed by the submission.

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8 FPVTE – FINGERPRINT MATCHING

Class Set Description # Images # Fingers Impression # Subjects

Search

A

S1 Right Index 1 1 Plain Mate: 10 000

Nonmate: 20 000

S2 Left Index 1 1 Plain Mate: 10 000

Nonmate: 20 000

S3 Left and Right Index 2 2 Plain Mate: 10 000

Nonmate: 20 000

B

S4 Right Slap IDFlat 1 4 Plain Mate: 10 000

Nonmate: 20 000

S5 Left Slap IDFlat 1 4 Plain Mate: 10 000

Nonmate: 20 000

S6 Left and Right Slap IDFlat 2

8

(4, 4)

Plain Mate: 10 000

Nonmate: 20 000

S7 Identification Flats 3

10

(4, 4, 2)

Plain Mate: 10 000

Nonmate: 20 000

C

S8 Ten Finger Rolled 10 10 Rolled Mate: 10 000

Nonmate: 20 000

S9 Ten Finger Plain 4

10

(4, 4, 1, 1)

Plain Mate: 10 000

Nonmate: 20 000

Enrollment

A

E1 Right Index 1 1 Plain 10 000

100 000

E2 Left Index 1 1 Plain 10 000

100 000

E3 Left and Right Index 2 2 Plain

100 000

500 000

1 600 000

B E4 Identification Flats 3

10

(4, 4, 2)

Plain

500 000

1 600 000

3 600 000

C

E5 Ten Finger Rolled 10 10 Rolled

500 000

1 600 000

3 000 000

5 000 000

E6 Ten Finger Plain 4

10

(4, 4, 1, 1)

Plain

500 000

1 600 000

3 000 000

5 000 000

Table 4: Search and enrollment datasets used in FpVTE. Class refers to the class of participation, as defined in Subsection 3.1. Set is an identifier used to uniquely identify the various FpVTE datasets in a concise manner. Description indicates

the finger combinations composing each dataset. # Images specifies the number of images per subject. # Fingers shows

the maximum number of fingers per subject. If a subject’s fingers were spread across multiple images, the maximum

number of fingers for each image is also shown. Impression refers to the impression type of the imagery in each dataset.

Impressions could be either plain or rolled, as defined in Subsection 3.2. # Subjects shows the number of subjects in each

dataset. For ’Search’ datasets, the value has been split into mate and nonmate subjects, referring to whether or not a known

mate for the subject exists in the corresponding enrollment set. For ’Enrollment’ datasets, the # Subjects show the various

enrollment set sizes planned for evaluation.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 9

3.4 “Size” of the Test

Class Enrollments

Performed

Subject to Subject

Comparisons

A 5.8 54

B 45.5 362

C 113 452

Table 5: Approximate number (in millions) of

enrollments and comparisons that were completed to evaluate each submission for that

class of participation.

The overall size of the test had implications on total run time. Table 5

shows the number of enrollments and comparisons that were completed

for each submission. Time limits allowed for a maximum of 3 seconds

per finger for each enrollment, and up to 500 seconds for Class A and 90

seconds for Class B and C to complete each search. Participants could

make two submissions for each class of participation. Three of the 18

participants submitted for Class A only, while the other 15 submitted

for all three classes, creating a total of 96 submissions analyzed in this

report. There were three rounds of submissions, with participants receiving results after the first two submissions to analyze before making

their next submission. Most submissions shared enrollment templates

between both submissions within a class, but two or three submissions in

each round required generating enrollment templates separately.

One unexpected event was that the majority of the submissions required re-enrolling the data for each round of submissions. Each round of submissions required approximately 2.5 billion fingerprint enrollments. It took two to three months

for each round of submissions to enroll all the data for all the submissions before searching could begin. The 30 000 (20 000

nonmate and 10 000 mate) searches took another one to two months to complete for each round of submissions for all

classes across all submissions and finger combinations. The first two rounds resulted in approximately 43 trillion subjectto-subject comparisons, and the final round will have approximately 470 trillion subject-to-subject comparisons. The final

submission will be the only one to do searching against variable enrollment set sizes. Total enrollment and search times

were slightly longer when accounting for submissions that failed in the middle of enrollment or matching and had to be

fixed and restarted (Subsection 4.4).

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
10 FPVTE – FINGERPRINT MATCHING

4 Experiment and Test Protocol

4.1 API Overview

The FpVTE API consisted of three major steps: feature extraction, finalization, and identification. During all steps of

the evaluation, participants had read-only access to a configuration directory, where configuration files, models, or other

algorithm-specific data could be stored. Not all participants made use of the configuration directory. It was made available as a convenience to those participants who did not wish to store customized traits about their software inside the

submission itself. In practice, many participants were able to perform changes, such as adjusting identification speed,

simply by changing a configuration file within this directory instead of needing to recompile their submission.

4.1.1 Feature Extraction

The first step in the FpVTE evaluation pipeline was feature extraction. During this step, software submissions were given

the opportunity to turn one or more images of fingerprints into a single fingerprint template. There were no requirements

on the format of the fingerprint template, as it was expected that the majority of participants would make use of proprietary template formats. The FpVTE API provided a way to distinguish between the images that would be used for

searching and the images used to compose the enrollment set, though participants were free to treat all images in the same

fashion.

For each instance of feature extraction, the FpVTE test driver called an initialization method a single time, giving the

submission an opportunity to load information that might be needed for feature extraction. After the initialization call,

the feature extraction method was called N times. The FpVTE API provided the finger position, impression type, NFIQ

value (no value provided for slap images), image dimensions, and raw image bytes for each input image during the call to

extract features. As output, participants were to return the finger position, an image quality value, a fingerprint template,

and the size of the fingerprint template as it would be stored in RAM. The RAM size was important to determine the

number of compute nodes needed during identification, because the size of the template on disk might be significantly

larger or smaller than the size of the template in RAM. Participants could optionally return a core and delta coordinate for

the image.

4.1.2 Finalization

As fingerprint templates were returned from feature extraction, the FpVTE test driver added them to a RecordStore (a

key-value pair storage mechanism of the Biometric Evaluation Framework). This allowed I/O operations to be excluded

when calculating the runtime of feature extraction, as well as to allow NIST to store the large quantity of template data in

the most efficient way on NIST’s hardware. Once all features were extracted from enrollment set fingerprint images, the

FpVTE test driver called an API method to “finalize” the enrollment set. Based on the sum of the sizes of templates in RAM,

NIST calculated the appropriate number of compute nodes and passed this information, along with the RecordStore of all

templates, to the finalization method. During this method, the submission was to divide the enrollment set into a partition

for each compute node, as well as perform any sort of indexing, statistics, or other pre-identification tasks required.

Unlike how NIST controlled the storage mechanism for templates in feature extraction, participants had full control of

how to store their finalized enrollment sets. In many cases, the size of the finalized enrollment set was either much larger

or much smaller than the sum of the fingerprint templates sizes returned from feature extraction as stored on disk.

4.1.3 Identification

Once the finalized set was created, its read-only root directory was provided to the identification methods. Searching

the finalized set for candidates occurred over two stages. The first stage was performed on separate compute nodes (if

necessary, as determined by the amount of RAM needed), potentially searching subsets of the enrollment set. Output from

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FPVTE – FINGERPRINT MATCHING 11

this first stage was coalesced and provided to the second stage, which took place on a single compute node. These two

stages of identification are described at length in Section 5.

4.2 Test Constraints

In order to complete the evaluation in a reasonable amount of time, as well as to mimic potential operational requirements,

certain constraints were placed on FpVTE submissions. All times are maximum averages over the pre-evaluation datasets

(Section 3), though NIST employed reasonable “cutoff” times to prevent processes from never completing. See Caveats

for additional information about timing.

. Operating System and Compilation Environment: All submitted implementations required 64-bit linkage and were

tested on CentOS 6.2 (kernel version 2.6.32-220.7.1.el6.x86_64). NIST linked participant submissions to the FpVTE

test driver written in C++ with GNU g++ 4.4.6-3, using glibcxx 3.4.13 and glibc 2.12.

. Evaluation Hardware: Timing computations were performed on a Dell M610 with two Intel X5690 3.47 GHz processors and 192 GB of RAM.

. Threaded Computations: Threaded computations were only allowed for the finalization step. All other functions

were not to perform multithreaded computations, as the FpVTE test driver handled parallelism efficiently on the

NIST compute nodes.

. Feature Extraction Time: Feature extraction was required to complete in 3 seconds or less for each input fingerprint.

A four-finger slap was counted as four input fingerprints.

. Finalization Time: Finalization of the enrollment set of fingerprint templates was required to complete in 12 hours

or less on a single compute node.

. Search Time: Search time is the combined time measurement for stage one and stage two identification (not including initialization times). For Class A data, searches needed to complete in under 500 seconds, though implementations that searched in under 20 seconds were reported separately. For Class B and Class C, all searches needed to

complete in under 90 seconds.

4.3 Biometric Evaluation Framework

The FpVTE test driver made use of several C++ classes that are part of the NIST Image Group’s Biometric Evaluation

Framework [11] designed to make writing code for running biometric evaluations easier and more efficient, especially

on NIST-owned equipment. Classes from the framework used in the FpVTE API included key-value pair file storage,

safe dynamic arrays, error handling, and more. While the framework was mainly provided to participants as a means of

interacting with the FpVTE API, many participants chose to use some classes internally in their submissions.

In order to process the massive amount of data required for the evaluation, the submission was executed as a scalable

parallel job. Within the NIST testbed, an implementation of the Message Passing Interface (MPI) [10] was used to execute

the evaluation test programs. By using the MPI software, the size of the parallel job (in terms of participating compute

nodes) can be matched to the size of the input dataset.

The framework supports parallelism by abstracting and hiding the lower-level communication, error handling, and other

facets of the MPI library. The framework application need only implement a few functions in order to become an MPI

parallel job. One feature of the framework is a set of classes that support the distribution of record keys, or key-value

pairs, across the computation cluster. Key distribution allows for driving the test where all nodes have local access to the

data. Key-value distribution has the advantage of running the job with the data source present only on a single node.

Configuration of the job is managed with a simple text file that specifies the input data source, logging system (either files

or a log server), and the number of data consumers assigned to each compute node. By using a configuration file, test

scripts were simpler to invoke, the probability of error was reduced, and replication of the test scenario was implicitly

provided.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
12 FPVTE – FINGERPRINT MATCHING

4.4 Validation

Participants were provided imagery from publicly available datasets in the same format as the full evaluation datasets.

These validation datasets were used to test implementation functionality before NIST performed the evaluation on a much

larger dataset. Participants ran a validation test with the provided data on their own systems and provided NIST with the

resulting candidate lists and scores from a set of pre-selected searches. NIST did the same on the machines used for the

full evaluation to confirm that both NIST and the participant produced the same results. Validation also provided a way

to make sure that participants were following the conventions of the evaluation, such as returning appropriate quality

values and numbers of candidates, among others.

Care was taken to make the validation process as simple as possible, to let the participant focus more on their submission

than about intricacies specific to FpVTE. To assist, NIST provided a minimal version of the FpVTE test driver software

used in the evaluation to aid participants through the expected calling structure of the evaluation API. Scripts were provided to compile the test driver and run the validation test. All a participant needed to do was create a properly named

software submission, run the script, and submit the generated results file to NIST. Additionally, a build of the Biometric

Evaluation Framework was provided, and many participants made use of features found in the framework in their API

implementations.

4.5 Pre-Evaluation

A timing test was performed to make sure no submission was in violation of the required time limits. First, a sample of the

evaluation dataset was enrolled using ten processes per compute node and the timing of those enrollments were evaluated

to make sure they did not exceed the average of three seconds per fingerprint. I/O time was not included during this step,

as all data was passed to and from the FpVTE test driver in memory. If the submission passed the enrollment timing test,

the full set of data was enrolled and finalized for matching. After enrollment, the next timing test was a random sample

of mated and nonmated searches matched against the maximum enrollment set for each evaluation class. If the average

search time on this sample test set, using a single process on each compute node, completed under the maximum time

limit, the full search set of 30 000 searches was performed. The formula used to compute the total search time was:

Ts = (t1 × b1) + t2 (1)

where t1 = average identification stage one time

b1 = number of blades required for identification stage one

t2 = identification stage two time

This formula allowed for a fair comparison between submissions that used one compute node for identification stage one

versus others that may have used two or more compute nodes to store the enrollment set. The formula was vetted with

the participants because it assumes that the enrollment set is evenly distributed across all identification stage one blades

and that search time is fairly linear versus enrollment set size.

Every attempt was made to use the same hardware and number of processes for every submission when reporting timing

results. Additionally, the hardware used for timing was dedicated to the FpVTE test driver process with no other jobs

running on the system except OS related processes.

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P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 13

4.6 Receiving Submissions

Every FpVTE submission received by NIST went through the FpVTE Validation and Pre-Evaluation processes before committing resources to complete the full evaluation. Figure 7 visualizes the submission process with a flowchart. Many

submissions underwent the process multiple times due to defects in the initial submission. Potential FpVTE software

submission defects that would require a resubmission include:

. submission incorrectly signed or encrypted;

. participant’s validation results differ from NIST’s;

. software errors during evaluation;

. maximum average time limit exceeded;

. invalid API implementation.

NIST provided no upper bound on the number of times that a participant could resubmit software in the event of a defect.

Unfortunately, this created an unpredictably large amount of additional work for NIST, through managing submissions,

helping participants debug, reporting status, and the like. Figure 6 details the number of non-debugging submissions

received from participants over the course of the evaluation. The general trend of participants not achieving a “valid”

submission on the first or second attempt ultimately played a part in forcing NIST to extend the original evaluation

deadlines. Class A Class B Class C

0

10

20

30

C D E F G H I J K L M O P Q S T U V C D E F G H I J K L M O P Q S T U V C D E F G H I J K L M O P Q S T U V

Participant

Number of Submissions

Round 1 Round 2 Round 3

Figure 6: Total number of non-debugging submissions received before the final deadline.

At the conclusion of the evaluation, 733 FpVTE validation submissions were received by NIST, including validation

submissions from participants who ultimately withdrew from the evaluation. For this total, a submission is considered

a discrete transmission of non-debugging software to NIST that required action by a NIST employee, on a per-class basis.

There were three rounds during which participants could make submissions. Participants were given an opportunity to

update their submissions at the end of the first two submission rounds. Because FpVTE was a black-box evaluation, NIST

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
14 FPVTE – FINGERPRINT MATCHING

ultimately had no idea what changes to the submissions were made. A number of submissions majorly regressed in their

lack of defects, so it can be anecdotally inferred that large portions or even entire submissions were changed by some

participants.

NIST imposed certain timing requirements on participants to ensure that the evaluation could be completed on NIST

hardware in a reasonable amount of time, as well as to mimic a possible operational constraint. Several participants tried

to tune their submissions to make use of the maximum amount of time, giving themselves a potential increase in overall

accuracy. While the back-and-forth between NIST and the participants did increase the runtime of the evaluation, timing

defects were the most understandable defect encountered in the evaluation and was primarily caused by NIST-based

evaluation restrictions, not participant error.

During the final submission, participants C, D, E, G, H, I, O, P, Q, and V provided one or more submissions that validated

and ran to completion without NIST encountering defects other than timing restrictions. Participants C, E, G, I, O, and

V met this requirement for all classes of participation in the final submission. Participant E was the only participant to

achieve no defects other than timing restrictions, for every class during all three submission periods.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 15

Validation

NIST provides sample input

data and evaluation source code.

Participants run their submissions linked to NIST source

code over provided input data.

Participants send blackbox submission and output

from sample data to NIST.

NIST runs black-box submission

over the same sample input data

in the real evaluation environment.

Check

results.

Pre-Evaluation

NIST runs the full evaluation

over a set of 2 000 images

from the evaluation dataset.

NIST generates all templates for evaluation dataset.

Perform timing test

with subset of searches.

Full Evaluation

Run remaining (30 000) searches.

Repeat searches for variable enrollment set sizes.

Report results.

Bad

Good

Crash

Too Slow

Crash

Good

Good

Good

Good

Figure 7: Evaluation workflow.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
16 FPVTE – FINGERPRINT MATCHING

5 Two-Stage Matching

The one-to-many identification step of FpVTE was divided into two distinct phases, under the expectation that storing

the entire enrollment set in RAM on a single compute node would not have been possible. While this was true for many

submissions, it did not hold true for all, especially with Class A data. Even if the submission’s enrollment set fit in the

RAM of a single compute node, the two-stage match technique was still used.

5.1 Enrollment Set Partitioning

NIST determined the amount of RAM needed to hold the entire enrollment set based on a size value returned per finger

during enrollment. In some cases, unique forms of compression were employed, which allowed submissions to use significantly less RAM during identification than reported during enrollment. In other cases, submissions reported very small

RAM requirements per finger, but underlying implementation details required significantly more RAM. This information

was volunteered by participants and documented in Section 9.

After the amount of required RAM was determined, NIST identified the number of compute nodes necessary to support

the RAM requirements. Compute nodes had 192 GB of RAM each (see Subsection 4.2 for more information). Submissions

were then invoked with a method asking them to “finalize” the set of enrollment templates for B compute nodes with a

maximum of 192 GB of RAM per node. This gave submissions an opportunity to partition or subdivide the enrollment set

into more manageable pieces on a per-compute node basis.

5.2 Identification — Stage One

Once the enrollment set had been partitioned, or “finalized,” the next step was to perform searches on each of the partitions. First, the submission’s identification initialization method was called before the first stage of matching. It was

expected that submissions would iterate over their enrollment set partition and load it into the RAM of the compute node

for faster access. Some submissions spent much longer than anticipated in this initialization method, and may have performed some additional binning or pruning that wasn’t otherwise executed during the partitioning step. It’s important to

note that the NIST evaluation compute nodes did not have swap enabled, and so the only memory that could have been

allocated was physical RAM.

After initialization, each search template was matched on each compute node specified during partitioning. To speed up

this process, the FpVTE test driver forked into multiple processes. Under Linux, fork is implemented using copy-on-write

pages, so as long as the submission’s child processes did not write to the RAM allocated during initialization, multiple

identification processes could run in parallel with access to the enrollment set in RAM without fear of RAM being over

allocated. Submissions were allocated a 4 GB RAM disk file system per compute node, where free-form data could be

written. A RAM disk was used to avoid timing I/O as part of the identification process. The FpVTE test driver later

persisted the data to a permanent storage device, and provided this data to the submission during the second stage of

identification.

If an submission failed to perform identification for any reason in the first stage of identification, it was marked as a

miss in stage two, which increased false negative identification rate but slightly decreased false positive identification rate

(Section 6).

5.3 Identification — Stage Two

After all compute nodes had finished the first stage of identification, the second stage was invoked. The submission’s

initialization method for the second stage was called, pointing the submission to the location of its partitioned enrollment

sets (Subsection 5.1) and the RAM disk data from identification stage one. Then, each search template was submitted to

stage two for final identification matching. This search method was to return a candidate list, not exceeding 100 candidates,

with corresponding similarity scores in descending order (where the candidate at rank 1 was the most similar). Each call

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FPVTE – FINGERPRINT MATCHING 17

to perform a search included a path to a directory rooted on a RAM disk file system, in which the FpVTE test driver placed

the submission’s output from stage one (Subsection 5.2).

There was no intended control on how the second stage of identification reached the final candidate list, but the search time

limit imposed on submissions combined both stage one and stage two search times (see Section 4 for detailed information

on timing constraints and calculations). Stage two could have been as simple as a sort of stage one results, or as complex

as an additional level of matching involving templates. Based on the timing figures observed during the evaluation, both

trivial and complex stage two implementations were used by FpVTE participants.

Stage two took place on an individual compute node, though the pool of search templates may have been partitioned and

searched on multiple compute nodes independently by the FpVTE test driver to increase throughput.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
18 FPVTE – FINGERPRINT MATCHING

6 Metrics

The detection error tradeoff (DET) characteristic curve [9] was the primary metric used for comparing accuracy in FpVTE.

Specific points along the DET were examined for making comparisons between submissions. For this initial results report,

the number of mate searches was limited to 10 000 and the number of nonmate searches was limited to 20 000 subjects,

restraining the smallest error rate that could be used with statistical confidence to 10−3.

In addition to the accuracy of the submission, this report compares speed and computational resource usage. Comparisons

between all submission are made and reported.

6.1 Accuracy

Open-set identification algorithms can make two types of recognition error:

. Search of a biometric sample of an individual not enrolled in the biometric enrollment set (a nonmated search) returns

the biometric reference identifier(s) attributable to one or more enrolled person. This is considered Type I, or false

alarm, because it returns a false identity.

. Search of a biometric sample of an enrolled individual (a mated search) returns an incorrect enrolled identity. This is

considered Type II, or miss, because it misses the correct identity.

FpVTE quantified the accuracy of the open-set identification algorithms as follows:

. False positive identification rate (FPIR), or Type I error rate, is the fraction of the nonmated searches where one or

more enrolled identities are returned at or above threshold (T) [4]. FPIR is a function of: the size of the enrollment

set (N), length of candidate lists (L), and score threshold (T). In the general case, this can be summarized as

FPIR(N, T, L) =

Number of searches with any nonmates returned

above threshold T on candidate list length L

Number of nonmated searches conducted

(2)

and more precisely notated for this evaluation as

FPIR(T) =

PQ

q=1 H(dq1 − T)

Q

(3)

where Q is the number of searches performed for which there exists no mate in the enrollment set, dq1 is the highest

similarity score reported by the algorithm for the q-th search. The function H(x) is the Heaviside step function

H(x) = (

0, if x < 0

1, if x ≥ 0

(4)

. False negative identification rate (FNIR), or Type II error rate, is the fraction of the mated searches where the enrolled mate is outside the top R rank or comparison score is below threshold (T). FNIR is a function of: the size

of the enrollment set (N), length of candidate lists (L), score threshold (T), and the number of top candidates being

considered (R). This is summarized in the general case as

FNIR(N, R, T, L) =

Number of mates outside top R ranks or below

threshold T on candidate list length L

Number of mated searches conducted

(5)

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FPVTE – FINGERPRINT MATCHING 19

and is defined formally for this evaluation as

FNIR(T) = 1 −

1

P

X

P

p=1

X

L

r=1

Ipr[1 − H(dpr − T)] (6)

where P is the number of searches performed for which there exists a mate in the enrollment set, dpr is the r-th

lowest similarity score reported by the algorithm for the p-th search, and Ipr is 1 if the identity of the r-th candidate

is the same as the identity of search p, or 0 otherwise.

Note that FNIR computation does not care about the cause of a miss: failure to correctly identify a sample (e.g., due to

poor quality), failure to extract a template, failure to generate a comparison score, and software crashes are all dealt with

similarly.

The terms “hit rate,” “reliability,” and “sensitivity” that have been mentioned in some literature on automated fingerprint

identification systems (AFIS) [8, 16] are just the complement of FNIR, computed as 1 − FNIR.

Another widely used accuracy metric is cumulative match characteristic (CMC), which is the fraction of the mated searches

where the enrolled mate is at rank R or better, regardless of its comparison score. CMC is a special case of FNIR, or more

precisely, hit rate, when the constraint on threshold is removed, as shown in Equation 7.

CMC(N, L, R) = 1 − FNIR(N, L, T = 0, R) (7)

Rank-one hit rate, CMC(N, L, R = 1), is the most common accuracy metric reported in academic and AFIS-related literature. While CMC is reported for the tested submissions, it is an inadequate accuracy metric because its makes strong or

weak hits indistinguishable by ignoring similarity scores, and does not report Type I errors.

6.2 DET Plots

DET characteristic curves are the primary accuracy metric for offline testing of biometric recognition algorithms. Each

point on a DET curve exhibits the false positive identification and false negative identification rates associated with a

certain threshold value. The DET curve spans the entire range of possible threshold values, which is normally the range

of the comparison scores. To reveal the dependence of FNIR and FPIR at a fixed threshold, the DET curves are connected

at points where FNIRs and FPIRs are observed at the same threshold values.

As it is conventional, DET curves are presented for FpVTE submission. In a DET curve, Type I error rates are plotted on

the x-axis and Type II error rates are plotted on the y-axis, giving uniform treatment to both types of error. Both axes

use a logarithmic scale, which spreads out the plot and better distinguishes different well-performing systems. When

calculating FPIR and FNIR, all ranks were considered (L = R = 100).

6.3 Failure to Extract or Match a Template

Failure to extract is the fraction of images for which a template is not generated. Template generation can fail for the

enrollment sample or the search sample. In both cases, failure to extract a template is included as a miss in the computation

of FNIR (see section 6.1).

Additionally, recognition algorithms fail to execute one-to-many searches to produce comparison scores. The result is that

a valid candidate list is not produced. Such failures might be voluntary (e.g., refusal to process a poor quality image) or

involuntary (e.g., software crashes). Either way, it is an undesirable behavior, and should be included in computation of

recognition errors, particularly to allow for fair comparison of submissions. FpVTE treated such failure cases as a miss

and added them to the Type II errors.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
20 FPVTE – FINGERPRINT MATCHING

Right Hand Left Hand

1 6

2 7

3 8

4 9

5 10

11 12

13 14

Table 6: Table showing which finger positions were swapped when

the images were flipped for nonmate

searches.

Figure 9: Example of flipped single-index finger

image.

6.4 Computational Efficiency

Another aspect of performance is the computational resources required by a submission. This report includes a comparison of template generation times, one-to-many search times, and template sizes for the submissions, along with their

accuracy at a set FPIR point of 10−3. The timing numbers are based on data samples for which all submissions were run

under identical conditions on the same hardware.

6.5 Ground Truth Errors

0 FNIR 1 0 FPIR 1

Figure 8: Example of a DET showing a spike in False Positive Identification Rate. This is usually a sign

of ground truth errors in nonmate

searches.

There were two types of ground truth errors that had to be resolved for FpVTE

datasets. The first involved nonmate searches that had an unknown mate in the

enrollment set. These errors would wrongly increase FPIR (see Section 6). The

second involved mated searches that did not match the presumed mate or had

other unknown mates in the enrollment set. Either of these mated search errors

could wrongly increase FNIR. An example of the effect on a DET curve is shown

in Figure 8. Once the errors show up at a certain threshold, the error rate sharply

increases and remains erroneously high.

The nonmate search errors were resolved by flipping fingerprint images on the

vertical axis for nonmated searches. In order to have the correct topography of the

finger, left/right hand labelings and finger positions were reversed after flipping.

Table 6 shows how the finger positions were swapped to keep the correct finger

topography. Example images are shown in Figure 9, Figure 10, and Figure 11.

The mated search errors had to be resolved through manual inspection. A large cause of the unknown mates resulted

from FpVTE using data from multiple sources. These ground truth errors had to be detected by examining the unexpected

high-scoring alleged nonmates produced by the submissions. The results from the submissions were grouped together

to determine which unexpected high-scoring alleged nonmates needed manual inspection. The first step was to look at

searches where all the submissions had an unexpected high-scoring alleged nonmate above a certain threshold. Next,

cases were examined for which only some of the submissions had a high-scoring alleged nonmate. After examining these

cases, if the majority were true mates, the thresholds used were decreased and the process repeated until very few or no

more true mates were found. Not all submissions were used for this process as some produced results that would have

required too much manual work to inspect all of the potential errors produced. This process was repeated for low scoring

alleged mates. The mate searches with low scores were examined to determine if the alleged mate was truly a mate or if

there was a ground truth error. Very low quality images were not removed from the datasets.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 21

Figure 10: Example of flipped left slap image. Note that the flipped image was used as a right slap.

Figure 11: Example of flipped right slap image. Note that the flipped image was used as a left slap.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
22 FPVTE – FINGERPRINT MATCHING

7 Accuracy Results

Subsections 7.1 through 3 show the identification accuracy results, from round 3 submissions, for all three classes of participation. The sections include plots sorted by rank for FNIR at a fixed FPIR of 10−3

, Detection Error Tradeoff (DET) curves

showing accuracy over a range of threshold values, Cumulative Match Characteristic (CMC) curves showing accuracy

over a range of candidate list ranks, and tables with FNIR values at a fixed FPIR. A complete set of full-size DET curves

for each participant are included in Appendix A. Appendix B shows DET and CMC plots for all submissions and classes

grouped on a single page.

This section (7) is followed by sections showing accuracy tradeoff results. Section 8 shows FNIR compared to search

time statistics. Appendix C and Appendix D have a complete set of tables for search time statistics. Appendix E shows

the progression of timing and results from the second to third round of submissions. Section 9 shows FNIR compared

to computational resources such as RAM usage and enrollment (i.e., template creation) times. Appendices F to H have

detailed tables on templates sizes and creation times.

These results are coalesced in Section 10, with tables combining ranked results for each category (FNIR, search time, RAM,

enrollment time). Appendix I has the complete set of tables for ranked results in all classes of participation. Appendix K

plots relative comparisons of FNIR, RAM usage, template creation times, and search times.

Section 11 combines results across classes of participation showing how accuracy varied based on the number of fingers

available for searching. Appendix J plots relative comparisons, by class, for each search set used in FpVTE.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 23

7.1 Class A

7.1.1 Single-Index Finger Identification

The accuracy of single-finger identification is shown with rank-sorted FNIR points (based on right index finger results) in

Figure 12, DET curves in Figure 13, CMC plots in Figure 14, and tables of FNIR points at a fixed FPIR in Tables 7 through

8.

Some observations for Class A single-finger identification include (all FNIR values are at FPIR =10−3):

. The most accurate submissions were D, Q, I, V and L2.

. The right index finger was more accurate than the left index finger.

. The most accurate submission D achieved a FNIR of 1.97% for the left index finger and 1.9% for the right index

finger searched against an enrollment set of 100 000 subjects.

. There is a measurable accuracy gap between the top performers and the next level of performers.

. The CMC plots in Figure 14 are not as flat as the other classes. This indicates that while most mates appear within

the top three candidates on the list, there are some that appear further down the list when using single-finger identification.

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D1 D2 I2 Q2 I1 Q1 V2 V1 L2 S1 S2 L1 T2 E2 E1 J2 O2 K1 K2 J1 O1 F2 G2 G1 F1 U1 U2 P2 C2 C1 P1 H1 H2 T1 M2 M1

Submission

FNIR @ FPIR =10−3

● Left Index ● Right Index

Figure 12: Rank-sorted FNIR @ FPIR = 10−3for Class A — Single Index Finger searching 30 000 subjects against 100 000

subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
24 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00500.01000.02000.05000.10000.20000.5000

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

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P

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Q

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

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0.0010

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0.0100

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 Left Index (1) Left Index (2) Right Index (1) Right Index (2)

Figure 13: DET for Class A — Single Index Finger searching 30 000 subjects against 100 000 subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
F

PVTE – FINGERPRINTMATCHING 25

Rank

Miss Rate

0.20000.10000.05000.02000.01000.00500.00200.0010

5 10 15 P

Q

5 10 15 S

T

5 10 15 U

V

I

J

K

L

M

O

0.20000.10000.05000.02000.01000.00500.00200.0010

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E

F

G

H

Left Index (1) Left Index (2) Right Index (1) Right Index (2)

Figure 14: CMC for Class A — Single Index Finger searching 30 000 subjects against 100 000 subjects. Submissions “1” and “2” from round 3.

C= afis teamD= 3M CogentE= NeurotechnologyF= PapillonG= DermalogH= Hisign Bio-Info Institute

I= NECJ= SondaK= Tiger ITL= InnovatricsM= SPEXO= ID Solutions

P= id3

Q= MorphoS= Decatur IndustriesT= BIO-keyU= AwareV= AA Technology
26 FPVTE – FINGERPRINT MATCHING

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 30 0.1335

C

2 31 0.1337

1 1 0.0197

D

2 1 0.0197

1 16 0.0745

E

2 15 0.0723

1 25 0.1111

F

2 22 0.1082

1 24 0.1089

G

2 23 0.1086

1 32 0.1576

H

2 33 0.1607

1 7 0.0257

I

2 8 0.0278

1 18 0.0786

J

2 14 0.0712

1 21 0.0883

K

2 20 0.0875

1 11 0.0625

L

2 9 0.0351

1 35 0.2995

M

2 34 0.2921

1 19 0.0818

O

2 17 0.0766

1 29 0.1308

P

2 28 0.1272

1 3 0.0222

Q

2 4 0.0226

1 10 0.0571

S

2 12 0.0650

1 36 NA

T

2 13 0.0685

1 27 0.1218

U

2 26 0.1178

1 6 0.0253

V

2 5 0.0252

Table 7: Tabulation of results for Class A — Left Index, with an

enrollment set size of 100 000. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier

used to differentiate between the two submissions each participant

could make. FNIR was computed at the score threshold that gave

FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 30 0.1132

C

2 29 0.1124

1 1 0.0190

D

2 1 0.0190

1 15 0.0630

E

2 14 0.0624

1 25 0.0933

F

2 22 0.0903

1 24 0.0910

G

2 23 0.0909

1 32 0.1230

H

2 33 0.1249

1 5 0.0215

I

2 3 0.0214

1 20 0.0708

J

2 16 0.0643

1 18 0.0682

K

2 19 0.0685

1 12 0.0505

L

2 9 0.0295

1 36 0.2615

M

2 35 0.2526

1 21 0.0776

O

2 17 0.0675

1 31 0.1133

P

2 28 0.1100

1 6 0.0218

Q

2 3 0.0214

1 10 0.0442

S

2 11 0.0503

1 34 0.1929

T

2 13 0.0562

1 26 0.0996

U

2 27 0.1007

1 8 0.0223

V

2 7 0.0222

Table 8: Tabulation of results for Class A — Right Index, with an

enrollment set size of 100 000. Letter refers to the participant’s letter

code found on the footer of this page. Sub. # is an identifier used

to differentiate between the two submissions each participant could

make. FNIR was computed at the score threshold that gave FPIR =

10−3. The number to the left of a value provides the value’s columnwise ranking, with the best performance shaded in green and the

worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 27

7.1.2 Two-Index Finger Identification

The accuracy of two-finger identification is shown with rank-sorted FNIR points in Figure 15, DET curves in Figure 16,

CMC plots in Figure 17, and a table of FNIR points at a fixed FPIR in Table 9.

Some observations for Class A two-finger identification include (all FNIR values are at FPIR =10−3):

. The most accurate submissions were Q, V, D, and I.

. The most accurate submission Q achieved a FNIR of 0.27% searched against an enrollment set of 1.6 million subjects.

. The accuracy gap between the top performers and the second tier, while still measurable, was not as large as singlefinger identification.

. Two-finger identification was far superior to single-finger identification and scaled to much larger enrollment sets.

. The CMC plots in Figure 17 flatten out faster than in single-finger identification. In most cases, the mate is within

the top three candidates of the list or doesn’t appear at all. There were a few submissions that extend down to the

top five to ten candidates.

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Q1 Q2 V2 D1 D2 I2 V1 I1 L2 J1 J2 L1 S2 E2 E1 O2 O1 S1 K2 G2 P2 U1 U2 K1 T2 C1 P1 C2 F1 F2 G1 H2 H1 M2 M1 T1

Submission

FNIR @ FPIR =10−3

● Left and Right Index

Figure 15: Rank-sorted FNIR @ FPIR = 10−3for Class A — Two Index Fingers searching 30 000 subjects against 1 600 000

subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
28 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

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Figure 16: DET for Class A — Two Index Fingers searching 30 000 subjects against 1 600 000 subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
F

PVTE – FINGERPRINTMATCHING 29

Rank

Miss Rate

0.20000.10000.05000.02000.01000.00500.00200.0010

5 10 15 P

Q

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T

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V

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0.20000.10000.05000.02000.01000.00500.00200.0010

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H

Left and Right Index (1) Left and Right Index (2)

Figure 17: CMC for Class A — Two Index Fingers searching 30 000 subjects against 1 600 000 subjects. Submissions “1” and “2” from round 3.

C= afis teamD= 3M CogentE= NeurotechnologyF= PapillonG= DermalogH= Hisign Bio-Info Institute

I= NECJ= SondaK= Tiger ITL= InnovatricsM= SPEXO= ID Solutions

P= id3

Q= MorphoS= Decatur IndustriesT= BIO-keyU= AwareV= AA Technology
30 FPVTE – FINGERPRINT MATCHING

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 26 0.0368

C

2 28 0.0374

1 4 0.0030

D

2 4 0.0030

1 15 0.0207

E

2 14 0.0202

1 29 0.0386

F

2 30 0.0412

1 31 0.0515

G

2 20 0.0311

1 33 0.0686

H

2 32 0.0684

1 8 0.0058

I

2 4 0.0030

1 10 0.0143

J

2 10 0.0143

1 24 0.0360

K

2 19 0.0286

1 12 0.0146

L

2 9 0.0072

1 35 NA

M

2 34 NA

1 17 0.0229

O

2 16 0.0214

1 27 0.0370

P

2 21 0.0333

1 1 0.0027

Q

2 1 0.0027

1 18 0.0281

S

2 13 0.0195

1 36 NA

T

2 25 0.0366

1 22 0.0336

U

2 23 0.0358

1 7 0.0034

V

2 3 0.0028

Table 9: Tabulation of results for Class A — Left and Right Index, with an enrollment set size of 1 600 000. Letter refers to the participant’s letter code

found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. FNIR was

computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The

number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 31

7.2 Class B

The accuracy results for Class B, which included four-finger, eight-finger, and ten-finger identification, are shown with

rank-sorted FNIR points (based on ten finger results) in Figure 18, DET curves in Figure 19, CMC plots in Figure 20, and

tables of FNIR points at fixed FPIR in Tables 10 through 13.

Some observations for Class B include (all FNIR values are at FPIR =10−3):

. The most accurate submissions with all ten fingers were I, Q, and D, with FNIRs ranging from 0.09% to 0.2%.

. The next level of submissions were V, E, L, J, O, and G, with FNIRs ranging from 0.24% to 0.4%. The separation

between the top performers and next level of performers was noticeably lower as more fingers are used.

. Right slaps (FNIR = 0.45%, I2) were more accurate than left slaps (FNIR = 0.94%, I2).

. Four-finger identification (FNIR = 0.45%) performed worse than two-finger identification (FNIR = 0.27%), as reported in Subsubsection 7.1.2. Two potential causes for this result are that the submissions in Class B had to perform

segmentation as part of the feature extraction process, and possibly a variation in image quality between the datasets.

Further study will be needed to determine the primary reason four-finger slaps performed worse than two index fingers.

. The matching accuracy improved significantly going from four fingers to eight fingers.

. The best submission I2 achieved FNIRs as follows: left slap (0.94%), right slap (0.45%), left and right slaps (0.15%),

and identification slaps (0.09%).

. The CMC plots in Figure 20 generally show very flat responses. This indicates that for most submissions, the mate

is within the top three candidates on the list or the mate doesn’t appear on the list at all.

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Submission

FNIR @ FPIR =10−3

● Identification Flats ● Left and Right Slap ● Left Slap ● Right Slap

Figure 18: Rank-sorted FNIR @ FPIR = 10−3for Class B — Left Slap, Right Slap, Left and Right Slap, and IDFlats searching

30 000 subjects against 3 000 000 subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
32 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.2000

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

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0.0005

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0.5000

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0.00100.00200.00500.01000.02000.05000.10000.2000 ● ●

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F

 Left Slap (2) Left Slap (1)

 Right Slap (2) Right Slap (1)

 Left and Right Slap (2) Left and Right Slap (1)

 Identification Flats (2) Identification Flats (1)

Figure 19: DET for Class B — Left Slap, Right Slap, Left and Right Slap, and IDFlats searching 30 000 subjects against 3 000 000 subjects. Submissions “1”and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
F

PVTE – FINGERPRINTMATCHING 33

Rank

Miss Rate

0.20000.10000.05000.02000.01000.00500.00200.0010

5 10 15 O

Q

5 10 15 S

U

5 10 15 V

G

H

I

J

L

0.20000.10000.05000.02000.01000.00500.00200.0010

M

C

D

E

F

Left Slap (1)Left Slap (2)

Right Slap (1)Right Slap (2)

Left and Right Slap (1)Left and Right Slap (2)

Identification Flats (1)Identification Flats (2) Figure 20: CMC for Class B — Left Slap, Right Slap, Left and Right Slap, and IDFlats searching 30 000 subjects against 3 000 000 subjects. Submissions “1” and “2” from round 3.

C= afis teamD= 3M CogentE= NeurotechnologyF= PapillonG= DermalogH= Hisign Bio-Info Institute

I= NECJ= SondaK= Tiger ITL= InnovatricsM= SPEXO= ID Solutions

P= id3

Q= MorphoS= Decatur IndustriesT= BIO-keyU= AwareV= AA Technology
34 FPVTE – FINGERPRINT MATCHING

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 22 0.0654

C

2 21 0.0647

1 6 0.0163

D

2 5 0.0142

1 13 0.0259

E

2 7 0.0187

1 29 0.1684

F

2 28 0.1681

1 18 0.0371

G

2 17 0.0325

1 23 0.0998

H

2 24 0.1008

1 4 0.0116

I

2 1 0.0094

1 15 0.0287

J

2 10 0.0236

1 16 0.0288

L

2 14 0.0276

1 30 0.1736

M

2 27 0.1634

1 12 0.0257

O

2 11 0.0254

1 2 0.0098

Q

2 3 0.0099

1 25 0.1089

S

2 26 0.1133

1 20 0.0500

U

2 19 0.0461

1 9 0.0192

V

2 8 0.0190

Table 10: Tabulation of results for Class B — Left Slap, with an enrollment set size of 3 000 000. Letter refers to the participant’s letter code

found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make.

FNIR was computed at the score threshold that gave FPIR = 10−3.

The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in

pink.

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 24 0.0403

C

2 23 0.0392

1 6 0.0072

D

2 2 0.0052

1 13 0.0151

E

2 7 0.0083

1 29 0.1222

F

2 28 0.1220

1 18 0.0212

G

2 16 0.0198

1 25 0.0641

H

2 26 0.0647

1 5 0.0058

I

2 1 0.0045

1 14 0.0156

J

2 10 0.0126

1 15 0.0167

L

2 17 0.0202

1 30 0.1259

M

2 27 0.1155

1 12 0.0142

O

2 11 0.0132

1 3 0.0057

Q

2 3 0.0057

1 21 0.0369

S

2 22 0.0381

1 19 0.0266

U

2 20 0.0273

1 8 0.0106

V

2 9 0.0110

Table 11: Tabulation of results for Class B — Right Slap, with an

enrollment set size of 3 000 000. Letter refers to the participant’s letter

code found on the footer of this page. Sub. # is an identifier used

to differentiate between the two submissions each participant could

make. FNIR was computed at the score threshold that gave FPIR =

10−3. The number to the left of a value provides the value’s columnwise ranking, with the best performance shaded in green and the

worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 35

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 30 NA

C

2 29 NA

1 6 0.0031

D

2 5 0.0024

1 15 0.0063

E

2 10 0.0049

1 28 0.0910

F

2 26 0.0901

1 18 0.0106

G

2 17 0.0084

1 23 0.0349

H

2 24 0.0361

1 3 0.0022

I

2 1 0.0015

1 16 0.0068

J

2 9 0.0047

1 12 0.0054

L

2 14 0.0062

1 27 0.0904

M

2 25 0.0882

1 13 0.0057

O

2 11 0.0051

1 2 0.0021

Q

2 3 0.0022

1 21 0.0160

S

2 22 0.0190

1 20 0.0139

U

2 19 0.0124

1 7 0.0036

V

2 7 0.0036

Table 12: Tabulation of results for Class B — Left and Right Slap, with

an enrollment set size of 3 000 000. Letter refers to the participant’s

letter code found on the footer of this page. Sub. # is an identifier

used to differentiate between the two submissions each participant

could make. FNIR was computed at the score threshold that gave

FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 30 NA

C

2 29 NA

1 6 0.0020

D

2 2 0.0012

1 16 0.0043

E

2 7 0.0024

1 27 0.0591

F

2 27 0.0591

1 18 0.0062

G

2 14 0.0040

1 23 0.0203

H

2 24 0.0204

1 2 0.0012

I

2 1 0.0009

1 17 0.0049

J

2 11 0.0033

1 10 0.0031

L

2 11 0.0033

1 26 0.0543

M

2 25 0.0515

1 15 0.0041

O

2 13 0.0035

1 2 0.0012

Q

2 2 0.0012

1 20 0.0108

S

2 21 0.0136

1 19 0.0099

U

2 22 0.0141

1 9 0.0027

V

2 7 0.0024

Table 13: Tabulation of results for Class B — Identification Flats, with

an enrollment set size of 3 000 000. Letter refers to the participant’s

letter code found on the footer of this page. Sub. # is an identifier

used to differentiate between the two submissions each participant

could make. FNIR was computed at the score threshold that gave

FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
36 FPVTE – FINGERPRINT MATCHING

7.3 Class C

The accuracy results for Class C, which included ten-finger identification for plain and rolled impression types using

scanned ink and livescan data, are shown with rank-sorted FNIR points (based on ten-finger rolled-to-rolled impression

results) in Figure 21, DET curves in Figure 22, CMC plots in Figure 23, and tables of FNIR points at a fixed FPIR in Tables 14

through 16.

Some observations for Class C include (all FNIR values are at FPIR =10−3):

. The most accurate submissions were I, Q, D, and V (ten-finger rolled-to-rolled), with FNIRs ranging from 0.1% to

0.19% for ten-finger plain impressions and ten-finger rolled impressions.

. There was not a clear difference between ten-finger plain-to-plain and ten-finger rolled-to-rolled results. This is a bit

of a surprise, as the ten-finger plain data had to be segmented by the submission and the ten-finger rolled data did

not. It also is a surprise after the observations of lower accuracy seen in Class B four-finger slaps versus the Class

A two index finger accuracy (Subsection 7.2). It might be interesting to perform a similar Class C test with only

four-finger slaps to see if the results are similar to Class B four-finger slap results.

. The second level of performers were E2, J, O, and V (ten-finger plain) with FNIRs ranging from 0.25% to 0.50% for

ten-finger plain-to-plain and ten-finger rolled-to-rolled impressions.

. The best performers were able to handle both rolled and plain impression images with little variation in FNIR, there

was a slight decrease when comparing plain-to-rolled impressions.

. Similar to Class B, the Class C CMC plots in Figure 23 are very flat, indicating the mate is within the top two positions

on the candidate list or it is completely missed.

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0.002

0.005

0.010

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0.050

0.100

0.200

I1 I2 Q2 D1 Q1 V1 D2 V2 J2 O2 O1 E2 J1 L2 C2 C1 L1 E1 H2 H1 G2 U2 U1 G1 F1 F2 M2 M1 S1 S2

Submission

FNIR @ FPIR =10−3

● Ten−Finger Plain−to−Plain ● Ten−Finger Plain−to−Rolled ● Ten−Finger Rolled−to−Rolled

Figure 21: Rank-sorted FNIR @ FPIR = 10−3

for Class C — Ten-Finger plain-to-plain, rolled-to-rolled, and plain-to-rolled

searching 30 000 subjects against 5 000 000 subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
F

PVTE – FINGERPRINTMATCHING 37

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005

0.0010

0.0020

0.0050

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0.0005

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0.0005

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0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005 ● ●

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F

 Ten−Finger Plain−to−Plain (1) Ten−Finger Plain−to−Plain (2)

 Ten−Finger Rolled−to−Rolled (1) Ten−Finger Rolled−to−Rolled (2)

 Ten−Finger Plain−to−Rolled (1) Ten−Finger Plain−to−Rolled (2) Figure 22: DET for Class C — Ten-Finger plain-to-plain, rolled-to-rolled, and plain-to-rolled searching 30 000 subjects against 5 000 000 subjects. Submis- sions “1” and “2” from round 3.

C= afis teamD= 3M CogentE= NeurotechnologyF= PapillonG= DermalogH= Hisign Bio-Info Institute

I= NECJ= SondaK= Tiger ITL= InnovatricsM= SPEXO= ID Solutions

P= id3

Q= MorphoS= Decatur IndustriesT= BIO-keyU= AwareV= AA Technology
38 FPVTE – FINGERPRINT MATCHING

Rank

Miss Rate

0.00100.00200.00500.01000.02000.05000.10000.2000

5 10 15

O Q

5 10 15

S U

5 10 15

V

G H I J L

0.00100.00200.00500.01000.02000.05000.10000.2000 M C D E F

Ten−Finger Plain−to−Plain (2)Ten−Finger Plain−to−Plain (1)

Ten−Finger Rolled−to−Rolled (2)Ten−Finger Rolled−to−Rolled (1)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Plain−to−Rolled (1)

Figure 23: CMC for Class C — Ten-Finger plain-to-plain, rolled-to-rolled, and plain-to-rolled searching 30 000 subjects against 5 000 000 subjects. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 39

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 30 NA

C

2 24 0.0711

1 6 0.0015

D

2 2 0.0011

1 14 0.0088

E

2 13 0.0048

1 25 0.0734

F

2 25 0.0734

1 23 0.0368

G

2 20 0.0276

1 20 0.0276

H

2 19 0.0275

1 4 0.0013

I

2 1 0.0010

1 12 0.0047

J

2 10 0.0027

1 16 0.0102

L

2 15 0.0095

1 28 0.0934

M

2 27 0.0826

1 9 0.0025

O

2 10 0.0027

1 2 0.0011

Q

2 4 0.0013

1 22 0.0311

S

2 29 0.1680

1 18 0.0163

U

2 17 0.0155

1 7 0.0024

V

2 7 0.0024

Table 14: Tabulation of results for Class C — Ten-Finger Plain-toPlain, with an enrollment set size of 5 000 000. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each

participant could make. FNIR was computed at the score threshold

that gave FPIR = 10−3. NA indicates that the operations required

to produce the value could not be performed. The number to the left

of a value provides the value’s column-wise ranking, with the best

performance shaded in green and the worst in pink.

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 16 0.0094

C

2 15 0.0085

1 4 0.0015

D

2 7 0.0018

1 18 0.0106

E

2 12 0.0050

1 25 0.0536

F

2 25 0.0536

1 24 0.0447

G

2 21 0.0333

1 20 0.0201

H

2 19 0.0199

1 1 0.0013

I

2 2 0.0014

1 13 0.0051

J

2 9 0.0033

1 17 0.0097

L

2 14 0.0083

1 28 0.0783

M

2 27 0.0716

1 11 0.0034

O

2 9 0.0033

1 5 0.0017

Q

2 2 0.0014

1 29 0.0860

S

2 30 0.2462

1 23 0.0358

U

2 22 0.0351

1 5 0.0017

V

2 8 0.0019

Table 15: Tabulation of results for Class C — Ten-Finger Rolled-toRolled, with an enrollment set size of 5 000 000. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each

participant could make. FNIR was computed at the score threshold

that gave FPIR = 10−3. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded

in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
40 FPVTE – FINGERPRINT MATCHING

Participant

FNIR @ FPIR = 10−3

Letter Sub. #

1 17 0.0149

C

2 18 0.0169

1 6 0.0028

D

2 3 0.0018

1 16 0.0137

E

2 12 0.0056

1 27 0.2514

F

2 27 0.2514

1 24 0.0649

G

2 23 0.0521

1 20 0.0291

H

2 19 0.0285

1 2 0.0014

I

2 1 0.0011

1 13 0.0071

J

2 7 0.0034

1 15 0.0136

L

2 14 0.0129

1 30 0.3067

M

2 27 0.2514

1 10 0.0041

O

2 8 0.0036

1 4 0.0020

Q

2 5 0.0022

1 25 0.1017

S

2 26 0.2366

1 22 0.0378

U

2 21 0.0295

1 11 0.0052

V

2 9 0.0039

Table 16: Tabulation of results for Class C — Ten-Finger Plain-to-Rolled, with an enrollment set size of 5 000 000. Letter refers to the participant’s letter

code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. FNIR was

computed at the score threshold that gave FPIR = 10−3. The number to the left of a value provides the value’s column-wise ranking, with the best

performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 41

8 Accuracy/Search Time Tradeoff

This section examines the tradeoff between FNIR and the amount of time each submission needed to perform identification

searches. The only time restriction placed on the submissions were they must complete searches before a maximum time

limit (Class A: 500 seconds, Class B/C: 90 seconds). NIST allowed for and encouraged two submissions per round. The

intent of this decision was to demonstrate the tradeoff between accuracy and speed, but there was no requirement that the

same basic algorithm be used for the intended “fast” and “slow” submission. It was possible that two completely different

algorithmic approaches were used by a participant, which could introduce other factors when comparing accuracy to

search time for a given participant. As such, the two submissions are simply labeled “1” and “2” in this report. The timing

tables shown in this section are based on the detailed timing tables in Appendix C that show the timing for each stage of

identification.

In addition to the accuracy/timing tradeoffs plots and timing tables in this section, Appendix E contains a full set of

tables that show timing changes that occurred between the last two rounds of submissions. Those tables provide more

data to analyze tradeoffs between search time and accuracy. Again, the algorithm could have changed from one round of

submissions to the next, but it is generally assumed that the basic algorithmic approach stayed the same, while “controls”

were tweaked to improve accuracy.

One general observation noticed across classes of participation was that increased search times are not a guarantee of

increased accuracy. This turned out to be inconsistent across the test. In general, most submissions obtain some improvement in accuracy with increased search times, but most gains are modest, and a few cases had no gain or a slight loss in

accuracy. There are other cases where submissions decreased search time yet still improved accuracy.

It might be useful in future evaluations to encourage competition over extremely fast searches and see which submissions

have a search time vs accuracy advantage, as opposed to tweaking for maximum accuracy, as was done in the current

FpVTE protocol.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
42 FPVTE – FINGERPRINT MATCHING

8.1 Class A

Tabulated comparisons of identification times for index finger identification submissions are shown in Tables 17 and 18.

The search times shown in these tables are from the “Total/One” column in Tables 24 through 29 included in Appendix C.

For reference, the FNIR values from Section 7 are reprinted to the right of the search times. Class A tables were split into

two groups. The first group includes submissions that performed searches on average in less than 20 seconds, and the

second includes those that took, on average, 20 seconds or longer.

The tables were used to create scatter plots showing accuracy, search times, and search template creation times. Those

plots are shown in Figures 24 through 29.

Some observations for Class A identification times include:

. For single index fingers, there was essentially no accuracy improvement observed with larger search times.

. For two index fingers, there was improvement shown by some participants with increased search time. The overall

benefit might depend on the application.

. It is difficult to compare single-finger identification results to two-finger identification results here, as the enrollment

set sizes used were not the same (100 000 and 1.6 million, respectively).

. The number of processes running (one or ten) didn’t appear to have a major effect on throughput for Class A single

index fingers, and only a slight increase in processing time was observed for two-finger searches. See Appendix C

and Appendix D for complete details.

. Tables 50 through 52 in Appendix E and Figures 30 through 35 show differences between the last two rounds of

submissions. Most submissions lowered FNIR for single finger but required longer search times. The results for two

index fingers were not as consistent. Most lowered FNIR, but some had a significant increase in search time for little

gain in FNIR. While it is not known what changes were made between submissions, there is some indication that

high accuracy can be achieved with some of the fast submissions. The absolute best accuracy is achieved by slightly

slower submissions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 43

Left Index (Less Than 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

5 10 15

H2

K1 O1 O2

P2

C1

E1 E2

G1

H1

I1

P1 U1

F1

K2

C2

D1

F2

J1 J2

L1

L2

M1 M2

Q2 Q1

S1

T1

T2

V1

● ●

●

● ●

● ● ●

● ●

●

●

●

●●

●

●

● ●

● ●

● ●

● ●

●

●

●

●

●

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Figure 24: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and median search time (less than 20 seconds) for a

single process for Class A — Left Index. The color of the data point is used to show the search template creation time. The color scale for search template

creation time is at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 17 and search

template creation times can be found in Table 72 in Appendix H.

Left Index (Greater Than or Equal To 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

10 20 30 40 50 60

D2

G2

I2

S2

U2

V2

●

●

●

●

●

●

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Figure 25: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 100 000 subjects and median search time (greater than or equal to 20

seconds) for a single process for Class A — Left Index. The color of the data point is used to show the search template creation time. The color scale

for search template creation time is at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from

Table 17 and search template creation times can be found in Table 72 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
44 FPVTE – FINGERPRINT MATCHING

Right Index (Less Than 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

5 10 15

F2

H2

J1 O2 K1

Q2

C1 H1

O1

P1

Q1

U1

F1 G1

I1

K2

C2

D1

E1 J2 E2

L1

L2

M1 M2

P2

S1

T1

T2

V1

● ●

●

● ●

● ● ●

● ●

●

●

● ●●

●

●

● ●

●

●

● ●

● ●

●

●

●

●

●

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Figure 26: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and median search time (less than 20 seconds) for a

single process. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the

top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 17 and search template creation times

can be found in Table 73 in Appendix H.

Right Index (Greater Than or Equal To 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

10 20 30 40 50 60

D2

G2

I2

S2

U2

● V2

●

●

●

●

●

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Figure 27: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 100 000 subjects and median search time (greater than or equal to 20

seconds) for a single process for Class A — Right Index. The color of the data point is used to show the search template creation time. The color scale

for search template creation time is at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from

Table 17 and search template creation times can be found in Table 73 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 45

Left and Right Index (Less Than 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.001

0.002

0.005

0.010

0.020

0.050

0.100

5 10 15

K1

O1

C1 C2

E1

G1

I1

L1 J1

V1

● ●

●

●

●

●

●

●

●

●

0 1 2 3 4 5

Figure 28: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and median search time (less than 20 seconds) for

a single process for Class A — Left and Right Index. The color of the data point is used to show the search template creation time. The color scale for

search template creation time is at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from

Table 18 and search template creation times can be found in Table 74 in Appendix H.

Left and Right Index (Greater Than or Equal To 20−Second Searches)

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.001

0.002

0.005

0.010

0.020

0.050

0.100

100 200 300 400 500

F2

L2

D2

E2

F1

Q2

U2

V2

S1

T2

D1

G2

H1 H2

I2

J2

K2

O2

P1 P2

Q1

S2

U1

● ●

●

● ●

●

● ●

●

●

●

●

●

●

●

● ●

●

●

●

● ●

●

0 1 2 3 4 5

Figure 29: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 1 600 000 subjects and median search time (greater than or equal to 20

seconds) for a single process for Class A — Left and Right Index. The color of the data point is used to show the search template creation time. The color

scale for search template creation time is at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are

from Table 18 and search template creation times can be found in Table 74 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
46 FPVTE – FINGERPRINT MATCHING

+ +

−

− −

− − −

+ +

−

−

−

− − + +

−

− −

−

+

−

0.02

0.05

0.10

0.20

C1 C2 D1 E1 E2 F1 F2 G1 H1 H2 I1 J1 J2 L1 L2 O1 O2 P2 Q1 Q2 S1 U1 V1

Submission

FNIR @ FPIR =10−3

0 5

Left Index (Less Than 20−Second Searches)

Figure 30: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Left Index. The “+” symbol indicates that FNIR increased from round 2

to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at

the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

−

−

+

−

−

0.02

0.05

0.10

D2 G2 I2 S2 V2

Submission

FNIR @ FPIR =10−3

10 20 30

Left Index (Greater Than or Equal To 20−Second Searches)

Figure 31: Plots showing difference in FNIR @ FPIR = 10−3

searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Left Index. The “+” symbol indicates that FNIR increased from round 2

to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at

the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 47

+ +

−

− −

− − −

+ +

−

− − − − +

+

−

− −

−

+

−

−

0.02

0.05

0.10

0.20

C1 C2 D1 E1 E2 F1 F2 G1 H1 H2 I1 J1 J2 L1 L2 O1 O2 P2 Q1 Q2 S1 T1 U1 V1

Submission

FNIR @ FPIR =10−3

−5 0 5

Right Index (Less Than 20−Second Searches)

Figure 32: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Right Index. The “+” symbol indicates that FNIR increased from round

2 to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at

the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

−

−

−

−

−

0.02

0.05

0.10

D2 G2 I2 S2 V2

Submission

FNIR @ FPIR =10−3

10 20 30

Right Index (Greater Than or Equal To 20−Second Searches)

Figure 33: Plots showing difference in FNIR @ FPIR = 10−3

searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Right Index. The “+” symbol indicates that FNIR increased from round

2 to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at

the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
48 FPVTE – FINGERPRINT MATCHING

+ +

−

−

−

−

+

− 0.005

0.010

0.020

0.050

0.100

C1 C2 G1 I1 J1 L1 O1 V1

Submission

FNIR @ FPIR =10−3

−40 −30 −20 −10 0

Left and Right Index (Less Than 20−Second Searches)

Figure 34: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Left and Right Index. The “+” symbol indicates that FNIR increased

from round 2 to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in

search time is at the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

−

−

− −

− + − + +

−

+

−

+

−

− −

− −

−

−

0.005 −

0.010

0.020

0.050

0.100

0.200

D1 D2 E1 E2 F1 F2 G2 H1 H2 I2 J2 L2 O2 P2 Q1 Q2 S1 S2 U1 U2 V2

Submission

FNIR @ FPIR =10−3

0 100 200 300

Left and Right Index (Greater Than or Equal To 20−Second Searches)

Figure 35: Plots showing difference in FNIR @ FPIR = 10−3

searching 30 000 subjects against 1 600 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class A — Left and Right Index. The “+” symbol indicates that FNIR increased

from round 2 to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in

search time is at the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 49

Participant Left Index Right Index

Letter Sub. # Time FNIR Time FNIR

< 20 seconds

1 1 0.26 24 0.1335 1 0.24 24 0.1132

C

2 6 0.76 25 0.1337 6 0.69 23 0.1124

D 1 20 7.32 1 0.0197 20 7.46 1 0.0190

1 3 0.35 12 0.0745 3 0.32 11 0.0630

E

2 30 16.90 11 0.0723 29 16.27 10 0.0624

1 11 2.49 20 0.1111 11 2.38 20 0.0933

F

2 14 3.56 18 0.1082 15 3.60 18 0.0903

G 1 21 9.74 19 0.1089 24 10.10 19 0.0910

1 15 3.61 26 0.1576 14 3.56 26 0.1230

H

2 17 4.13 27 0.1607 17 4.05 27 0.1249

I 1 22 9.94 5 0.0257 22 9.83 3 0.0215

1 4 0.54 14 0.0786 4 0.51 16 0.0708

J

2 7 1.25 10 0.0712 7 1.13 12 0.0643

1 25 10.44 17 0.0883 26 10.42 14 0.0682

K

2 23 10.32 16 0.0875 25 10.27 15 0.0685

1 2 0.29 8 0.0625 2 0.26 8 0.0505

L

2 12 3.32 6 0.0351 13 3.26 6 0.0295

1 10 1.84 29 0.2995 10 1.78 30 0.2615

M

2 26 10.70 28 0.2921 21 9.39 29 0.2526

1 5 0.62 15 0.0818 5 0.56 17 0.0776

O

2 9 1.56 13 0.0766 9 1.36 13 0.0675

1 8 1.32 23 0.1308 8 1.24 25 0.1133

P

2 13 3.33 22 0.1272 12 3.07 22 0.1100

1 28 15.70 2 0.0222 28 14.24 4 0.0218

Q

2 24 10.43 3 0.0226 23 9.98 2 0.0214

S 1 29 16.86 7 0.0571 30 16.55 7 0.0442

1 16 3.99 30 NA 16 3.73 28 0.1929

T

2 18 5.97 9 0.0685 19 5.87 9 0.0562

U 1 27 14.42 21 0.1218 27 10.76 21 0.0996

V 1 19 6.01 4 0.0253 18 5.60 5 0.0223

≥ 20 seconds

D 2 3 41.84 1 0.0197 2 28.64 1 0.0190

G 2 5 54.03 5 0.1086 5 59.55 5 0.0909

I 2 2 40.99 3 0.0278 3 40.35 2 0.0214

S 2 4 44.66 4 0.0650 4 46.05 4 0.0503

U 2 1 24.16 6 0.1178 1 20.10 6 0.1007

V 2 6 65.35 2 0.0252 6 61.24 3 0.0222

Table 17: Tabulation of median identification times for Class A. Submissions were split into two groups. The first group includes submissions that

performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The Time column shows the time used to perform a search over an enrollment set of 100 000. Time values are median times reported in seconds,

but were originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA indicates that the

operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
50 FPVTE – FINGERPRINT MATCHING

Participant Left and Right Index

Letter Sub. # Time FNIR

< 20 seconds

1 1 2.08 7 0.0368

C

2 4 6.35 8 0.0374

G 1 3 5.22 9 0.0515

I 1 8 17.87 2 0.0058

J 1 6 13.64 3 0.0143

K 1 9 18.01 6 0.0360

L 1 2 2.19 4 0.0146

O 1 7 14.46 5 0.0229

V 1 5 9.29 1 0.0034

≥ 20 seconds

1 15 70.99 4 0.0030

D

2 23 237.43 4 0.0030

1 1 16.35 11 0.0207

E

2 27 518.11 10 0.0202

1 13 60.66 21 0.0386

F

2 16 73.95 22 0.0412

G 2 22 221.16 15 0.0311

1 8 36.71 24 0.0686

H

2 12 52.25 23 0.0684

I 2 25 338.88 4 0.0030

J 2 7 33.35 8 0.0143

K 2 6 32.93 14 0.0286

L 2 3 23.42 7 0.0072

1 5 31.44 26 NA

M

2 20 171.24 25 NA

O 2 10 43.53 12 0.0214

1 14 63.65 20 0.0370

P

2 17 101.16 16 0.0333

1 21 212.69 1 0.0027

Q

2 19 161.02 1 0.0027

1 2 23.00 13 0.0281

S

2 26 495.50 9 0.0195

1 4 25.68 27 NA

T

2 9 37.23 19 0.0366

1 11 45.51 17 0.0336

U

2 24 240.40 18 0.0358

V 2 18 127.65 3 0.0028

Table 18: Tabulation of median identification times for Class A. Submissions were split into two groups. The first group includes submissions that

performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The Time column shows the time used to perform a search over an enrollment set of 1 600 000. Time values are median times reported in seconds,

but were originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA indicates that the

operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 51

8.2 Class B

Tabulated comparisons of identification times for IDFlat submissions are shown in Table 19. The search times shown in

this table are from the “Total/One” column in Tables 30 through 33 included in Appendix C. For reference, the FNIR

values from Section 7 are reprinted to the right of the identification times.

The tables were used to create scatter plots showing accuracy, search times, and search template creation times. Those

plots are shown in Figures 36 through 39.

Some observations for Class B identification times include:

. Most submissions had some improvement in accuracy with longer search times.

. Results vary, but some submissions (D, G, I1, Q1) performed searches faster when more fingers were available, while

others (H, L, S) required longer search times with more fingers.

. Most search times increased modestly when ten processes were running in parallel, compared to the single process

timing test. See Appendix C and Appendix D for complete details.

. Tables 30 through 33 in Appendix E and Figures 40 through 43 show differences between the last two rounds of

submissions. There are a variety of results in these tables. Again, most had improvement in FNIRs, but some with

longer search times and some with dramatically shorter search times. Like Class A, there are certainly indications

that high accuracy can be achieved with some fast submissions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
52 FPVTE – FINGERPRINT MATCHING

Left Slap

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

20 40 60 80

C2

D2

H2

J2

M1

V1 D1

G2

I1

L1

M2

O1

S2

U1

V2

F1

H1

O2

Q1

U2 C1

E1

E2

F2

G1

I2

L2 J1

Q2

S1

● ●

●

●

●

●

● ●

●

●

● ●

●

●

●

●

● ●

● ●

● ●

●●

●●

● ●

● ●

0 2 4 6 8 10 12 14

Figure 36: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and median search time for a single process for Class

B — Left Slap. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the

top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 19 and search template creation times

can be found in Table 75 in Appendix H.

Right Slap

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

20 40 60 80

C2

H2

L2

O1

Q1

D1

G2

I1

L1

M1

O2

Q2

S2

V2

H1

U2 U1

V1

C1

D2

E1

E2

F1 F2

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0 2 4 6 8 10 12 14

Figure 37: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 3 000 000 subjects and median search time for a single process for Class

B — Right Slap. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the

top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 19 and search template creation times

can be found in Table 76 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 53

Left and Right Slap

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.0005

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0.0020

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20 40 60 80

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0 5 10 15 20 25

Figure 38: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and median search time for a single process for Class

B — Left and Right Slap. The color of the data point is used to show the search template creation time. The color scale for search template creation time is

at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 19 and search template creation

times can be found in Table 77 in Appendix H.

IDFlat

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

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20 40 60 80

D2 Q2

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0 5 10 15 20

Figure 39: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 3 000 000 subjects and median search time for a single process for Class

B — Identification Flats. The color of the data point is used to show the search template creation time. The color scale for search template creation time is

at the top of the plot. Median search times are plotted in seconds. The FNIR and median search time data are from Table 19 and search template creation

times can be found in Table 78 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
54 FPVTE – FINGERPRINT MATCHING

− −

−

−

−

−

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+ +

−

−

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−

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+

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−

0.01

0.02

0.05

0.10

0.20

C1 C2 D1 D2 E1 E2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 M2 O1 O2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

0 20 40

Left Slap

Figure 40: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class B — Left Slap. The “+” symbol indicates that FNIR increased from round 2 to

round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at the

top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

+ +

− −

−

−

− −

+ +

−

−

−

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0.005

0.010

0.020

0.050

0.100

C1 C2 D1 D2 E1 E2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 M2 O1 O2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−20 0 20 40

Right Slap

Figure 41: Plots showing difference in FNIR @ FPIR = 10−3

searching 30 000 subjects against 3 000 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class B — Right Slap. The “+” symbol indicates that FNIR increased from round 2

to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at

the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 55

− −

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D1 D2 E1 E2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 M2 O1 O2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−20 0 20 40

Left and Right Slap

Figure 42: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class B — Left and Right Slap. The “+” symbol indicates that FNIR increased from

round 2 to round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search

time is at the top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

− −

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D1 D2 E1 E2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 M2 O1 O2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−40 −20 0 20 40

Identification Flats

Figure 43: Plots showing difference in FNIR @ FPIR = 10−3

searching 30 000 subjects against 3 000 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class B — IDFlat. The “+” symbol indicates that FNIR increased from round 2 to

round 3 and “-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at the

top of the plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
56 FPVTE – FINGERPRINT MATCHING

Participant Left Slap Right Slap Left and Right Slap Identification Flats

Letter Sub. # Time FNIR Time FNIR Time FNIR Time FNIR

1 2 3.74 22 0.0654 2 3.67 24 0.0403 3 6.40 30 NA 3 7.92 30 NA

C

2 4 6.74 21 0.0647 4 6.50 23 0.0392 5 10.70 29 NA 4 10.21 29 NA1 18 52.23 6 0.0163 19 53.32 6 0.0072 20 61.24 6 0.0031 17 45.15 6 0.0020

D

2 22 58.10 5 0.0142 21 57.19 2 0.0052 21 63.05 5 0.0024 18 46.70 2 0.00121 1 2.82 13 0.0259 1 2.97 13 0.0151 2 6.12 15 0.0063 2 6.76 16 0.0043

E

2 10 34.37 7 0.0187 10 34.47 7 0.0083 10 33.09 10 0.0049 15 43.61 7 0.00241 8 30.09 29 0.1684 8 31.87 29 0.1222 9 27.27 28 0.0910 12 37.56 27 0.0591

F

2 14 43.59 28 0.1681 15 45.92 28 0.1220 12 36.36 26 0.0901 20 49.34 27 0.05911 6 16.24 18 0.0371 5 10.13 18 0.0212 1 3.89 18 0.0106 1 4.26 18 0.0062

G

2 23 59.49 17 0.0325 13 37.28 16 0.0198 11 34.55 17 0.0084 6 16.26 14 0.00401 16 49.75 23 0.0998 17 50.16 25 0.0641 25 70.38 23 0.0349 26 82.66 23 0.0203

H

2 17 51.77 24 0.1008 18 52.84 26 0.0647 26 73.06 24 0.0361 27 86.56 24 0.02041 21 55.96 4 0.0116 20 55.87 5 0.0058 13 37.19 3 0.0022 7 19.07 2 0.0012

I

2 13 38.26 1 0.0094 14 41.13 1 0.0045 17 46.13 1 0.0015 16 43.86 1 0.00091 7 25.61 15 0.0287 7 24.14 14 0.0156 7 26.15 16 0.0068 8 25.38 17 0.0049

J

2 27 74.38 10 0.0236 27 74.09 10 0.0126 24 69.28 9 0.0047 22 60.13 11 0.00331 3 5.56 16 0.0288 3 5.47 15 0.0167 4 10.48 12 0.0054 5 14.50 10 0.0031

L

2 5 12.37 14 0.0276 6 12.66 17 0.0202 6 20.78 14 0.0062 9 28.59 11 0.00331 9 31.17 30 0.1736 9 32.03 30 0.1259 8 27.15 27 0.0904 13 38.87 26 0.0543

M

2 29 87.21 27 0.1634 29 87.41 27 0.1155 16 45.91 25 0.0882 23 65.91 25 0.05151 12 37.01 12 0.0257 12 35.61 12 0.0142 14 38.34 13 0.0057 11 35.64 15 0.0041

O

2 26 73.15 11 0.0254 26 73.93 11 0.0132 23 68.46 11 0.0051 21 60.02 13 0.00351 19 53.24 2 0.0098 23 64.04 3 0.0057 22 65.02 2 0.0021 14 42.92 2 0.0012

Q

2 20 54.02 3 0.0099 22 61.94 3 0.0057 19 53.40 3 0.0022 24 66.01 2 0.00121 24 71.69 25 0.1089 24 70.54 21 0.0369 29 83.33 21 0.0160 29 87.60 20 0.0108

S

2 25 71.77 26 0.1133 25 70.84 22 0.0381 27 82.13 22 0.0190 30 88.46 21 0.01361 28 80.03 20 0.0500 30 89.26 19 0.0266 30 83.62 20 0.0139 28 86.60 19 0.0099

U

2 30 89.07 19 0.0461 28 80.11 20 0.0273 28 82.40 19 0.0124 25 75.28 22 0.01411 11 36.07 9 0.0192 11 35.43 8 0.0106 15 38.93 7 0.0036 10 34.96 9 0.0027

V

2 15 47.97 8 0.0190 16 48.51 9 0.0110 18 52.80 7 0.0036 19 49.30 7 0.0024

Table 19: Tabulation of median identification times for Class B. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between

the two submissions each participant could make. The Time column shows the time used to perform a search over an enrollment set of 3 000 000. Time values are median times reported in

seconds, but were originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3

. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 57

8.3 Class C

Tabulated comparisons of identification times for ten-finger identification submissions are shown in Table 20. The search

times shown in this table are from the “Total/One” column in Tables 34 through 36 included in Appendix C. For reference,

FNIR values from Section 7 are reprinted to the right of the identification times.

The tables were used to create scatter plots showing accuracy, search times, and search template creation times. Those

plots are shown in Figure 44.

Some observations for Class C identification times include:

. Like classes A and B, gains varied across the participants, but most had some level of improvement in accuracy with

longer search times.

. Results for some submissions varied between ten-finger plain-to-plain and ten-finger rolled-to-rolled impressions.

Some were faster with plain impressions and others were faster with rolled impressions. The most accurate submissions appeared to match both types accurately.

. Tables 34 through 36 in Appendix E and Figure 45 show differences between the last two rounds of submissions.

Like classes A and B, these results indicate that high accuracy can be achieved with some fast submissions, but the

absolute best accuracy was not the fastest submission.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
58 FPVTE – FINGERPRINT MATCHING

Plain−to−Plain

Median Search Time − One Process (seconds)

FNIR @ FPIR =10

−

3

0.0005

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0.0020

0.0050

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20 40 60 80

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Figure 44: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and median search time for a single process for Class

C. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the top of the plot.

Median search times are plotted in seconds. The FNIR and median search time data are from Table 20 and search template creation times can be found

in Tables 79 and 80 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 59

+

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C2 D1 D2 E1 E2 F1 F2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−20 0 20 40

Ten−Finger Plain−to−Plain

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C1 C2 D1 D2 E1 E2 F1 F2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−60 −40 −20 0 20 40

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C1 C2 D1 D2 E1 E2 F1 F2 G1 G2 H1 H2 I1 I2 J1 J2 L1 L2 Q1 Q2 V1

Submission

FNIR @ FPIR =10−3

−40 −20 0 20

Ten−Finger Plain−to−Rolled

Figure 45: Plots showing difference in FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and difference in search times, for a

single search process, between round 2 and round 3 submissions for Class C. The “+” symbol indicates that FNIR increased from round 2 to round 3 and

“-” indicates a decrease in FNIR. The color of the bar shows the change in search time. The color scale for difference in search time is at the top of the

plot and the units are in seconds. The data for the plots are taken from the tables in Appendix E.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
60 FPVTE – FINGERPRINT MATCHING

Participant Ten-Finger Plain-to-Plain Ten-Finger Rolled-to-Rolled Ten-Finger Plain-to-Rolled

Letter Sub. # Time FNIR Time FNIR Time FNIR

1 4 18.30 30 NA 4 20.15 16 0.0094 6 33.68 17 0.0149

C

2 5 18.38 24 0.0711 6 21.97 15 0.0085 8 34.85 18 0.0169

1 25 73.93 6 0.0015 17 58.92 4 0.0015 13 41.67 6 0.0028

D

2 26 74.36 2 0.0011 27 74.97 7 0.0018 16 57.36 3 0.0018

1 2 12.77 14 0.0088 2 8.63 18 0.0106 1 8.99 16 0.0137

E

2 17 52.91 13 0.0048 11 42.73 12 0.0050 7 34.06 12 0.0056

1 15 51.69 25 0.0734 16 55.79 25 0.0536 19 58.57 27 0.2514

F

2 18 60.86 25 0.0734 20 68.20 25 0.0536 21 61.87 27 0.2514

1 1 7.71 23 0.0368 1 7.78 24 0.0447 2 16.78 24 0.0649

G

2 7 23.69 20 0.0276 3 19.46 21 0.0333 4 22.14 23 0.0521

1 21 68.07 20 0.0276 30 84.51 20 0.0201 22 64.83 20 0.0291

H

2 20 65.36 19 0.0275 29 84.50 19 0.0199 23 65.74 19 0.0285

1 16 52.41 4 0.0013 15 54.56 1 0.0013 15 52.47 2 0.0014

I

2 10 38.28 1 0.0010 7 30.82 2 0.0014 12 41.48 1 0.0011

1 12 43.57 12 0.0047 9 33.02 13 0.0051 9 38.41 13 0.0071

J

2 28 77.75 10 0.0027 19 67.98 9 0.0033 25 67.88 7 0.0034

1 3 17.51 16 0.0102 8 31.68 17 0.0097 5 27.47 15 0.0136

L

2 6 23.53 15 0.0095 5 20.25 14 0.0083 3 20.18 14 0.0129

1 11 43.37 28 0.0934 12 48.08 28 0.0783 17 57.63 30 0.3067

M

2 13 46.70 27 0.0826 13 48.80 27 0.0716 18 57.91 27 0.2514

1 23 68.54 9 0.0025 14 54.42 11 0.0034 20 59.05 10 0.0041

O

2 24 73.41 10 0.0027 21 69.30 9 0.0033 24 66.80 8 0.0036

1 9 36.86 2 0.0011 26 74.40 5 0.0017 11 39.76 4 0.0020

Q

2 8 35.35 4 0.0013 25 74.22 2 0.0014 10 39.37 5 0.0022

1 29 86.56 22 0.0311 22 69.71 29 0.0860 30 88.48 25 0.1017

S

2 30 91.74 29 0.1680 23 70.77 30 0.2462 29 88.07 26 0.2366

1 27 74.94 18 0.0163 28 82.61 23 0.0358 28 82.88 22 0.0378

U

2 22 68.30 17 0.0155 24 72.48 22 0.0351 27 74.56 21 0.0295

1 14 47.02 7 0.0024 10 40.74 5 0.0017 14 48.40 11 0.0052

V

2 19 62.26 7 0.0024 18 65.07 8 0.0019 26 69.87 9 0.0039

Table 20: Tabulation of median identification times for Class C. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. The Time column shows the time used to perform a search

over an enrollment set of 5 000 000. Time values are median times reported in seconds, but were originally recorded to microsecond precision. The FNIR

column shows FNIR for each submission at FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The

number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 61

9 Accuracy Computational Resources Tradeoff

This section discusses the computational resources used by each submission, mainly looking for trends in accuracy of a

submission versus the load it created on the compute nodes. Statistics include how large the stored/finalized templates

are on disk versus in memory and how much time it took to create feature templates. Detailed tables in Appendix F show

enrollment set sizes, in Appendix G show search template sizes, and in Appendix H show template creation times. All

these tables were used to create the scatter plots used in this section. Appendix K plots relative comparisons of FNIR,

RAM usage, template creation times, and search times.

Addtionally, all the numbers in Tables 60 through 65 in Appendix F are based on the maximum enrollment set sizes for

each class shown in Table 4. The RAM values reported are the best estimate based on the information recorded. It is

possible that a submission used more or less RAM depending on the internal operations of the submitted software. See

the Lessons Learned for Large-Scale Testing section for more details.

9.1 Storage and Memory

It is important to note that the Actual RAM used (Appendix F) is the sum of the resident enrollment set sizes of identification stage one processes after returning from the identification stage one initialization method. More information on this

can be found in the FpVTE API [15].

Every attempt was made to run each submission on the minimum number of compute nodes needed to successfully

complete the evaluation. This generally meant multiple passes of running enrollment set finalization and redoing timing

validation tests to determine the minimum number of compute nodes needed. If too few compute nodes were used, the

submission would crash and not work properly.

When looking at the results, there are submissions like those from participant Q that had large finalized enrollment set,

but used a lot less Actual RAM during stage one identification. In fact, Q always ran on a single compute node despite

the Finalized storage size. Participant L, on the other hand, clearly compressed templates, so they used more Actual RAM

than Finalized storage. This behavior was pre-reported to NIST, which made it easier to plan ahead when testing the

submission.

9.1.1 Class A

Scatter plots comparing FNIR and computational resources used by index finger identification submissions are shown in

Figures 46 through 51.

Figures 52 through 53 shows a comparison of the templates (right and left index) as stored on disk with the actual size

used in RAM. For the majority of participants, the numbers were very similar but there were exceptions such as T, P, G,

L, and Q.

Some observations for Class A computational resources include:

. The most accurate submissions were Q, V, I, D and L2.

. The most accurate submissions used the same or less RAM as other submissions with I2 being an exception.

. It appears that high accuracy can be achieved without using a large amount of storage.

. Participant T’s submissions consistently used the least computational resources but with the least accuracy.

. Of the most accurate submissions, participant V used the least amount of storage space.

. Participant K consumed the most RAM and disk space, significantly higher than all other participants.

. Participant Q used the least amount of RAM and achieved the highest accuracy of the most accurate submissions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
62 FPVTE – FINGERPRINT MATCHING

Left Index

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

1 2 3

C2

D2

E2

F2 G2

H2

O2

P2

T1

T2

V2

G1

I1

K1

M1

O1

P1

S2

V1

C1

E1

F1

H1

J1

Q2

D1

I2

J2

K2

L1

L2

M2

Q1

S1

U2 U1

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0 1 2 3 4 5

Figure 46: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and RAM used for enrollment set for Class A — Left

Index. The color of the data point is used to show the On Disk Finalized Enrollment Size. The color scale for the On Disk Finalized Enrollment Size is at the

top of the plot and the units are in gigabytes. The data for the scatter plot comes from Table 60 in Appendix F. RAM Used for Enrollment Set is from the

RAM/Actual column and On Disk Finalized Enrollment is from the On Disk/Finalized column.

Right Index

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

1 2 3

D2

E2

G2

H1

M2

O2

P2

T1

T2

V1

C1

G1

H2

I1

K2

M1

O1

P1

S2

V2

C2

E1

F1

J1

Q1

D1

F2

I2

J2 K1

L1

L2

Q2

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U2 U1

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●

0 1 2 3 4 5

Figure 47: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 100 000 subjects and RAM used for enrollment set for Class A — Right

Index. The color of the data point is used to show the On Disk Finalized Enrollment Size. The color scale for the On Disk Finalized Enrollment Size is at the

top of the plot and the units are in gigabytes. The data for the scatter plot comes from Table 61 in Appendix F. RAM Used for Enrollment Set is from the

RAM/Actual column and On Disk Finalized Enrollment is from the On Disk/Finalized column.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 63

Left Index

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

2000 4000 6000 8000 10000

C2

D2

E2

F2

H2

K2

M2

O2

V2

G2

I1

O1

P1

Q2

C1 U2

D1

E1

F1

H1

J1 K1

M1

S2

V1

G1

I2

J2

L1

L2

P2

Q1

S1

T1

T2

U1

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0 2000 4000 6000 8000 10000

Figure 48: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and search template size in RAM for Class A — Left

Index. The color of the data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is at the top of the plot

and the units are in bytes. On Disk comes from table Table 66 in Appendix G.

Right Index

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.01

0.02

0.05

0.10

0.20

0.50

2000 4000 6000 8000 10000

C2

E2

F2

H1

I1

M2

O2

D2

G2

H2

K2 O1

P1

Q2

U1

V2

C1

F1

I2

J1 K1

M1

S2

D1

E1

G1

J2

L1

L2

P2

Q1

S1

T1

T2

U2

V1

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0 2000 4000 6000 8000 10000

Figure 49: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and search template size in RAM for Class A — Right

Index. The color of the data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is at the top of the plot

and the units are in bytes. On Disk comes from table Table 66 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
64 FPVTE – FINGERPRINT MATCHING

Left and Right Index

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.001

0.002

0.005

0.010

0.020

0.050

0.100

20 40 60

C2

H2

J2

T2

V2

D1

E1

F2

G1

G2

K1

O1

P1

Q1

V1

F1

H1

J1

C1

D2

E2

I1

I2

K2

L1

L2

O2

P2

Q2

S1

S2

U2 U1

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0 10 20 30 40 50 60 70

Figure 50: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and RAM used for enrollment set for Class A — Left

and Right Index. The color of the data point is used to show the On Disk Finalized Enrollment Set size. The color scale for the On Disk Finalized Enrollment

Set is at the top of the plot and the units are in gigabytes. The data for the enrollment set size comes from Table 62 in Appendix F. RAM used for Enrollment

Set is from the RAM/Actual column and On Disk Finalized Enrollment Set is from the On Disk/Finalized column.

Left and Right Index

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.001

0.002

0.005

0.010

0.020

0.050

0.100

5000 10000 15000 20000

C2

E2

H2

I1

J2

K2

U1

V2

D1

E1

F2

G1

O1

P1

Q1

U2

V1

F1

H1

I2

J1

K1

S1

S2

C1

D2

G2

L1

L2

O2

P2

Q2

T2

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0 5000 10000 15000 20000

Figure 51: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 1 600 000 subjects and search template size in RAM. The color of the

data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is at the top of the plot and the units are in bytes.

On Disk comes from Table 66 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 65

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C

E

F

G H

J

K

M

P O

S Q

T

V

D1

D2

I1

L1 L2 I2 U1

U2

32 MB

1 GB

32 GB

1 GB 4 GB 16 GB 64 GB

Finalized Directory Size

Actual RAM Consumption

Left and Right Index

Figure 52: Comparison of enrollment size in RAM and on disk. The x- and y-axes use log scales. The data for enrollment size comes from Table 62 in

Appendix F. Actual RAM Consumption is from the RAM/Actual column and Finalized Directory Size is from the On Disk/Finalized column.

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C

D

E

F

G

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K

M

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P Q

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T

U

V

I1

I2

L1

L2

0 B

5 kB

10 kB

15 kB

20 kB

0 B 5 kB 10 kB 15 kB 20 kB

Disk Size

RAM Size

Left and Right Index

Figure 53: Comparison of search template size in RAM and on disk. On Disk comes from Table 66 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
66 FPVTE – FINGERPRINT MATCHING

9.1.2 Class B

Scatter plots comparing FNIR and computational resources used by IDFlat identification submissions are shown in Figures 54 through 55.

Figures 56 through 57 shows a comparison of the templates as stored on disk with the actual size used in RAM. Like class

A results, this plot highlights submissions where on disk and in RAM usage differed such as E, G, L, and Q.

Some observations for Class B computational resources include:

. The lowest RAM usage is also one of the top performers (Q).

. Other top performers (participants D and I) do not have the largest RAM usage.

. Participant I cut RAM usage in half with minimal drop in accuracy.

. Like Class A, high accuracy can be achieved while keeping RAM usage relatively low.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 67

IDFlat

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

100 200 300 400 500

D1

F1

H2

L1 L2 O1

S1

V1

F2

G1

G2

J1

Q2

S2 U2

E1

H1

M1

O2

V2

C1 C2

D2

E2

I1

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J2

M2

Q1

U1

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0 100 200 300 400 500 600

Figure 54: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and RAM used for enrollment set for Class B —

Identification Flats. The color of the data point is used to show On Disk Finalized Enrollment Set size. The color scale for the on disk finalized enrollment

size is at the top of the plot and the units are in gigabytes. The data for the enrollment set size comes from Table 63 in Appendix F. RAM Used for

Enrollment Set is from the RAM/Actual column and On Disk Finalized Enrollment Set is from the On Disk/Finalized column.

IDFlat

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

20000 40000 60000 80000

C2

F2

O2

U2

D1

F1

G1

H2

J1

L2

Q2

S2

V1

C1

M1

O1

S1

D2

E1

E2

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H1

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L1 J2

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0 10000 20000 30000 40000 50000 60000 70000 80000

Figure 55: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 3 000 000 subjects and search template size in RAM for Class B —

Identification Flats. The color of the data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is at the top

of the plot and the units are in bytes. On Disk comes from Table 67in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
68 FPVTE – FINGERPRINT MATCHING

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C

F D

G

H

J

M

O

Q

S

E1 V

E2

I1

L1 I2

L2

U1

U2

8 GB

16 GB

32 GB

64 GB

128 GB

256 GB

512 GB

32 GB 64 GB 128 GB 256 GB 512 GB

Finalized Directory Size

Actual RAM Consumption

Identification Flats

Figure 56: Comparison of enrollment size in RAM and on disk for Class B — Identification Flats. The x- and y-axes use log scales. The data for

enrollment size comes from Table 63 in Appendix F. Actual RAM Consumption is from the RAM/Actual column and Finalized Directory Size is from the

On Disk/Finalized column.

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E1

E2

I1

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U2

15 kB

30 kB

45 kB

60 kB

19 kB 38 kB 57 kB 76 kB

Disk Size

RAM Size

Identification Flats

Figure 57: Comparison of search template size in RAM and on disk for Class B — Identification Flats. On Disk comes from Table 67 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 69

9.1.3 Class C

Scatter plots comparing FNIR and computational resources used by plain and rolled impression submissions are shown

in Figures 58 through 61.

Figures 62 through 65 show a comparison of the templates as stored on disk with the actual size used in RAM. Like class

A and B results, these plot highlight submissions where on disk and in RAM usage differed for several submissions.

Some observations for Class C computational resources include:

. Like classes A and B, the top performers do not use the largest amount of RAM.

. High accuracy can be achieved with relatively low RAM usage.

. Ten-finger rolled data used more RAM than ten-finger plain data, but is not more accurate.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
70 FPVTE – FINGERPRINT MATCHING

Plain

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

200 400 600 800

C1

C2

D1

D2

H2

J2

Q1

G1

I1

J1

M1

O2

Q2

U1

V1

F1

H1

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Figure 58: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and RAM used for enrollment set for Class C —

Ten-Finger Rolled-to-Rolled. The color of the data point is used to show the On Disk Finalized Enrollment Set size. The color scale for the On Disk Finalized

Enrollment Size is at the top of the plot and the units are in gigabytes. The data for the scatter plot comes from Table 64 in Appendix F. RAM used for

Enrollment Set is from the RAM/Actual column and On Disk Finalized Enrollment Set is from the On Disk/Finalized column.

Rolled

RAM Used for Enrollment Set (gigabytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

200 400 600 800

F2

H2

I2

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D2

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C1

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0 100 200 300 400 500 600 700 800 900

Figure 59: Scatter plot of FNIR @ FPIR = 10−3

searching 30 000 subjects against 5 000 000 subjects and RAM used for enrollment set for Class C —

Ten-Finger Rolled-to-Rolled. The color of the data point is used to show the On Disk Finalized Enrollment Set size. The color scale for the On Disk Finalized

Enrollment Size is at the top of the plot and the units are in gigabytes. The data for the scatter plot comes from Table 65 in Appendix F. RAM used for

Enrollment Set is from the RAM/Actual column and On Disk Finalized Enrollment Set is from the On Disk/Finalized column.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 71

Plain

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

20000 40000 60000 80000 100000 120000

C2

D2

F1

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G1

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L1

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Q2

U1

V1

C1

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0 20000 40000 60000 80000 100000 120000 140000

Figure 60: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and search template size in RAM for Class C —

Ten-Finger Plain-to-Plain. The color of the data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is at

the top of the plot and the units are in bytes. On Disk comes from Table 68 in Appendix G.

Rolled

Search Template Size Per Subject In RAM (bytes)

FNIR @ FPIR =10

−

3

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

20000 40000 60000 80000 100000 120000

D2

F2 G1

G2

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0 20000 40000 60000 80000 100000 120000 140000

Figure 61: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and search template size in RAM for Class C —

Ten-Finger Rolled-to-Rolled. The color of the data point is used to show Search Template Size On Disk. The color scale for Search Template Size On Disk is

at the top of the plot and the units are in bytes. On Disk comes from Table 68 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
72 FPVTE – FINGERPRINT MATCHING

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16 GB

32 GB

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128 GB

256 GB

512 GB

64 GB 128 GB 256 GB 512 GB 1 TB

Finalized Directory Size

Actual RAM Consumption

Ten−Finger Plain Impression

Figure 62: Comparison of enrollment size in RAM and on disk for Class C — Plain Impression. The x- and y-axes use log scales. The data for enrollment

size comes from Table 64 in Appendix F. Actual RAM Consumption is from the RAM/Actual column and Finalized Directory Size is from the On

Disk/Finalized column.

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20 kB 40 kB 60 kB 80 kB

Disk Size

RAM Size

Ten−Finger Plain Impression

Figure 63: Comparison of search template size in RAM and on disk for Class C — Plain Impression. On Disk comes from Table 68 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 73

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Figure 64: Comparison of enrollment size in RAM and on disk for Class C — Rolled Impression. The x- and y-axes use log scales. The data for

enrollment size comes from Table 65 in Appendix F. Actual RAM Consumption is from the RAM/Actual column and Finalized Directory Size is from the On

Disk/Finalized column.

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Figure 65: Comparison of search template size in RAM and on disk for Class C — Rolled Impression. On Disk comes from Table 68 in Appendix G.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
74 FPVTE – FINGERPRINT MATCHING

9.2 Processing Time

This section shows the time required to enroll fingerprints images also referred to as template creation time. The template

creation times were recorded by enrolling a common sample of the datasets on common hardware, with 100 processes

running in parallel across 10 compute nodes (10 processes per compute node). Any segmentation time for slap captures

was included in the template creation times.

The detailed tables (Tables 72 and 80) used to make the scatter plots (Figures 66 through 71) in this section are included in

Appendix H. The Enrollment columns give some idea as to the required system capacity needed to enroll a large dataset in

a reasonable time frame. As an example, if a submission takes the full time allowed per image (3 seconds) and 16 compute

nodes are used for the enrollment process, it will take approximately 16 days to process all the enrollment sets for all three

classes.

In an operational sense, enrollment only occurs a single time for the entire dataset, and then on an as-needed basis when

new subjects are added to the dataset. The Search columns are different, as they show the time needed to create a template

every time a new search is performed. This time would be factored in as part of the overall search time process.

Some observations from tables and plots include:

. The most accurate submissions did not have the fastest enrollment times. In fact, the best performers tend to have

longer enrollment times.

. Enrollment time appears to be proportional to finger type and impression. For example, single-finger captures are

faster than ten-finger plain impressions, which are faster than ten-finger rolled impressions.

. Segmentation does not appear to significantly increase enrollment times, as noted by comparing ten-finger plain

impressions to ten-finger rolled impressions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 75

Left Index

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Figure 66: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and enrollment template creation time for Class A —

Left Index. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the top of

the plot and the units are in seconds. The template creation time data is from Table 72 in Appendix H.

Right Index

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Figure 67: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 100 000 subjects and enrollment template creation time for Class A —

Right Index. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at the top

of the plot and the units are in seconds. The template creation time data is from Table 73 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
76 FPVTE – FINGERPRINT MATCHING

Left and Right Index

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Figure 68: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 1 600 000 subjects and enrollment template creation time for Class A —

Left and Right Index. The color of the data point is used to show the search template creation time. The color scale for search template creation time is

at the top of the plot and the units are in seconds. The template creation time data is from Table 74 in Appendix H.

IDFlat

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Figure 69: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 3 000 000 subjects and enrollment template creation time for Class B —

Identification Flats. The color of the data point is used to show the search template creation time. The color scale for search template creation time is at

the top of the plot and the units are in seconds. The template creation time data is from Table 78 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 77

Plain

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Figure 70: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and enrollment template creation time for Class C –

Ten-Finger Plain-to-Plain. The color of the data point is used to show the search template creation time. The color scale for search template creation time

is at the top of the plot and the units are in seconds. The template creation time data is from Table 79 in Appendix H.

Rolled

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Figure 71: Scatter plot of FNIR @ FPIR = 10−3searching 30 000 subjects against 5 000 000 subjects and enrollment template creation time for Class C –

Ten-Finger Rolled-to-Rolled. The color of the data point is used to show the search template creation time. The color scale for search template creation

time is at the top of the plot and the units are in seconds. The template creation time data is from Table 80 in Appendix H.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
78 FPVTE – FINGERPRINT MATCHING

10 Ranked Results

This section combines tables from Sections 7 and 9 into a single table. The resulting tables are rank-sorted based on FNIR

values.

There is one table from each class of participation included in the main body of this report. The full set of tables for all

classes and search set scenarios are included in Appendix I.

These tables are useful because they combine all the high-level information in a single table. They are rank-sorted on FNIR,

as accuracy is generally considered the most important goal for an identification algorithm to achieve. The reader can then

look across and see how a participant ranked in other areas such as search time (Identification), search template creation

time (Search Enrollment), and memory usage (RAM). As stated in previous sections, the most accurate submissions are

not the fastest. In all three classes, there is a two to three times increase in the error rate when comparing the most accurate

submission with one of the top three fastest in search speed.

Appendix K plots relative comparisons of FNIR, RAM usage, template creation times, and search times.

Appendix L is one attempt to take the tables in this section and apply some relative weight or importance to each column.

The tables in Appendix L use these weights to produce a score for each submission and then sort the results based on

those scores. Refer to Appendix L for more details.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 79

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

< 20 seconds

V 1 1 0.0034 5 9.50 5 9.29 4 0.68 3 0.64 5 11.77

I 1 2 0.0058 9 18.92 8 17.87 9 2.96 9 2.93 6 15.83

J 1 3 0.0143 6 14.00 6 13.64 3 0.66 4 0.65 3 8.30

L 1 4 0.0146 1 2.20 2 2.19 1 0.11 1 0.11 8 18.76

O 1 5 0.0229 7 15.34 7 14.46 2 0.55 2 0.53 4 9.05

K 1 6 0.0360 8 18.32 9 18.01 8 2.11 8 2.09 9 61.81

C 1 7 0.0368 2 2.39 1 2.08 5 0.80 5 0.78 2 4.87

C 2 8 0.0374 4 6.34 4 6.35 5 0.80 5 0.78 1 4.87

G 1 9 0.0515 3 6.27 3 5.22 7 1.13 7 1.09 7 16.38

≥ 20 seconds

Q 1 1 0.0027 21 213.08 21 212.69 16 1.13 15 1.08 10 9.14

Q 2 1 0.0027 19 163.65 19 161.02 16 1.13 15 1.08 9 9.14

V 2 3 0.0028 18 133.45 18 127.65 10 0.68 9 0.64 13 11.77

I 2 4 0.0030 25 385.14 25 338.88 27 4.37 27 4.30 21 30.83

D 2 4 0.0030 23 234.52 23 237.43 26 3.12 26 2.84 17 18.58

D 1 4 0.0030 16 73.01 15 70.99 25 3.10 25 2.84 17 18.58

L 2 7 0.0072 3 23.54 3 23.42 3 0.33 3 0.31 26 53.98

J 2 8 0.0143 7 36.19 7 33.35 9 0.66 10 0.65 7 8.30

S 2 9 0.0195 26 429.02 26 495.50 18 1.77 18 1.75 14 14.82

E 2 10 0.0202 27 500.30 27 518.11 11 0.70 11 0.70 23 33.41

E 1 11 0.0207 2 22.27 1 16.35 11 0.70 11 0.70 22 33.40

O 2 12 0.0214 10 45.52 10 43.53 4 0.55 4 0.53 8 9.05

S 1 13 0.0281 1 20.11 2 23.00 18 1.77 18 1.75 14 14.82

K 2 14 0.0286 6 32.68 6 32.93 20 2.11 20 2.09 27 61.81

G 2 15 0.0311 22 227.27 22 221.16 15 1.13 17 1.09 16 16.38

P 2 16 0.0333 17 114.37 17 101.16 13 0.77 13 0.72 19 21.41

U 1 17 0.0336 11 47.60 11 45.51 1 0.30 1 0.30 25 44.63

U 2 18 0.0358 24 252.04 24 240.40 1 0.30 1 0.30 24 37.35

T 2 19 0.0366 9 38.91 9 37.23 5 0.65 7 0.62 1 0.01

P 1 20 0.0370 14 63.41 14 63.65 13 0.77 13 0.72 20 21.42

F 1 21 0.0386 13 59.30 13 60.66 21 2.23 21 2.15 5 4.86

F 2 22 0.0412 15 71.45 16 73.95 21 2.23 21 2.15 5 4.86

H 2 23 0.0684 12 53.77 12 52.25 7 0.66 5 0.60 11 9.36

H 1 24 0.0686 8 37.65 8 36.71 7 0.66 5 0.60 12 9.36

M 2 25 NA 20 183.20 20 171.24 23 2.25 23 2.16 4 3.76

M 1 26 NA 5 32.59 5 31.44 23 2.25 23 2.16 3 3.75

T 1 27 NA 4 26.96 4 25.68 5 0.65 7 0.62 1 0.01

Table 21: Tabulation of ranked results for Class A — Left and Right Index. Submissions were split into two groups. The first group includes submissions

that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The FNIR column was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value

could not be performed. The Identification column shows the time used to perform a search over an enrollment set of 1 600 000, as seen in Table 18. The

Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 74. Identification and Search Enrollment

durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage

one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in Table 62. RAM is

reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
80 FPVTE – FINGERPRINT MATCHING

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0009 20 60.01 16 43.86 30 19.36 30 19.36 21 108.71

Q 1 2 0.0012 14 48.85 14 42.92 20 8.89 20 8.92 1 7.54

Q 2 2 0.0012 24 71.67 24 66.01 20 8.89 20 8.92 2 7.54

I 1 2 0.0012 6 24.57 7 19.07 25 16.50 25 16.52 5 49.68

D 2 2 0.0012 19 54.37 18 46.70 24 11.90 24 11.86 13 79.43

D 1 6 0.0020 17 52.42 17 45.15 17 6.19 17 6.16 12 79.43

V 2 7 0.0024 15 49.72 19 49.30 3 3.35 7 3.36 9 63.53

E 2 7 0.0024 18 52.88 15 43.61 16 5.95 16 5.93 28 317.95

V 1 9 0.0027 10 35.51 10 34.96 3 3.35 7 3.36 8 63.53

L 1 10 0.0031 5 14.42 5 14.50 2 3.05 2 3.05 22 119.79

L 2 11 0.0033 8 28.56 9 28.59 1 0.88 1 0.88 27 177.48

J 2 11 0.0033 22 64.38 22 60.13 7 3.38 3 3.35 17 101.00

O 2 13 0.0035 21 63.87 21 60.02 5 3.38 5 3.36 20 101.00

G 2 14 0.0040 9 31.67 6 16.26 18 7.89 18 7.90 26 156.12

O 1 15 0.0041 11 37.04 11 35.64 5 3.38 5 3.36 19 101.00

E 1 16 0.0043 2 8.76 2 6.76 13 5.35 13 5.34 14 79.73

J 1 17 0.0049 7 26.31 8 25.38 7 3.38 3 3.35 18 101.00

G 1 18 0.0062 1 6.33 1 4.26 18 7.89 18 7.90 25 156.12

U 1 19 0.0099 30 88.83 28 86.60 15 5.90 15 5.82 29 440.68

S 1 20 0.0108 28 86.50 29 87.60 22 10.24 22 10.31 24 150.35

S 2 21 0.0136 29 88.70 30 88.46 22 10.24 22 10.31 23 150.35

U 2 22 0.0141 25 80.14 25 75.28 14 5.80 14 5.73 30 540.60

H 1 23 0.0203 26 82.43 26 82.66 9 4.37 9 4.37 15 86.46

H 2 24 0.0204 27 85.74 27 86.56 9 4.37 9 4.37 16 86.46

M 2 25 0.0515 23 70.45 23 65.91 26 18.36 28 18.11 6 57.53

M 1 26 0.0543 13 41.37 13 38.87 26 18.36 28 18.11 6 57.53

F 1 27 0.0591 12 39.12 12 37.56 28 18.36 26 18.07 10 77.02

F 2 27 0.0591 16 51.59 20 49.34 28 18.36 26 18.07 10 77.02

C 2 29 NA 4 10.28 4 10.21 11 5.16 11 5.13 4 46.49

C 1 30 NA 3 9.00 3 7.92 11 5.16 11 5.13 3 46.49

Table 22: Tabulation of ranked results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of this page. Sub.

# is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score threshold

that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The Identification column shows the

time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The Search Enrollment column shows the time used to create a

search template to be used for a query, as seen in Table 78. Identification and Search Enrollment durations are reported in seconds, but were originally

recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after

returning from the identification stage one initialization method, as seen in Table 63. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824

bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 81

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 1 1 0.0013 24 79.04 15 54.56 25 20.21 25 20.23 4 113.80

Q 2 2 0.0014 27 83.35 25 74.22 17 12.95 17 13.06 2 20.22

I 2 2 0.0014 9 40.53 7 30.82 24 18.72 24 18.73 11 137.03

D 1 4 0.0015 17 65.97 17 58.92 23 17.44 21 17.39 10 132.40

Q 1 5 0.0017 26 83.25 26 74.40 17 12.95 17 13.06 1 20.22

V 1 5 0.0017 10 40.94 10 40.74 9 8.48 9 8.50 17 234.03

D 2 7 0.0018 30 86.39 27 74.97 30 30.43 30 30.47 9 132.37

V 2 8 0.0019 16 65.47 18 65.07 9 8.48 9 8.50 18 234.03

O 2 9 0.0033 19 72.55 21 69.30 6 6.80 6 6.71 23 303.13

J 2 9 0.0033 20 72.62 19 67.98 8 6.82 8 6.74 24 303.13

O 1 11 0.0034 15 59.01 14 54.42 6 6.80 6 6.71 25 303.13

E 2 12 0.0050 14 57.02 11 42.73 11 9.89 11 9.91 30 930.48

J 1 13 0.0051 8 36.09 9 33.02 5 6.78 5 6.69 22 303.13

L 2 14 0.0083 3 19.52 5 20.25 3 4.36 3 4.36 26 367.82

C 2 15 0.0085 5 25.91 6 21.97 13 10.79 13 10.69 15 183.36

C 1 16 0.0094 4 25.25 4 20.15 13 10.79 13 10.69 14 183.36

L 1 17 0.0097 7 31.42 8 31.68 3 4.36 3 4.36 21 280.49

E 1 18 0.0106 1 9.52 2 8.63 12 9.90 12 9.92 16 191.66

H 2 19 0.0199 29 84.26 29 84.50 15 12.08 15 12.17 12 144.02

H 1 20 0.0201 28 84.14 30 84.51 15 12.08 15 12.17 13 144.02

G 2 21 0.0333 6 30.61 3 19.46 19 15.55 19 15.50 19 261.29

U 2 22 0.0351 23 74.39 24 72.48 1 2.94 1 2.87 28 806.17

U 1 23 0.0358 25 82.76 28 82.61 1 2.94 1 2.87 28 806.17

G 1 24 0.0447 2 11.67 1 7.78 19 15.55 19 15.50 20 261.29

F 1 25 0.0536 13 55.63 16 55.79 28 21.07 28 20.92 7 130.29

F 2 25 0.0536 18 68.61 20 68.20 28 21.07 28 20.92 6 130.29

M 2 27 0.0716 12 48.71 13 48.80 26 21.02 26 20.89 5 130.29

M 1 28 0.0783 11 47.38 12 48.08 26 21.02 26 20.89 8 130.29

S 1 29 0.0860 22 74.01 22 69.71 21 17.43 22 17.57 27 382.88

S 2 30 0.2462 21 72.95 23 70.77 21 17.43 22 17.57 3 78.28

Table 23: Tabulation of ranked results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the

score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set of 5 000 000, as seen

in Table 20. The Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 80. Identification and

Search Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set

sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in

Table 65. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
82 FPVTE – FINGERPRINT MATCHING

11 How Many Fingers are Needed

It is already well known that using more fingers results in a lower FNIR [17]. This section combines the results from

Figures 12, 15, 18, and 21 into a single plot in Figure 72.

The reader is reminded that enrollment set sizes were 100 000 subjects for single index fingers, 1.6 million subjects for two

index fingers, 3 million subjects for IDFlats, and 5 million for ten-finger rolled and plain impressions. The search set size

was 30 000 that included 20 000 nonmate and 10 000 mate searches.

Additionally, Appendix J plots relative comparisons, by class, for each search set used in FpVTE.

Some observations regarding numbers of fingers include:

. More fingers were better and produced the most accurate results.

. More fingers took more time to enroll (Subsection 9.2)

. Ten-finger plain-to-plain impressions were as accurate as ten-finger rolled-to-rolled impressions with higher performing submissions.

. More fingers generally produce faster search times against very large enrollment sets (Section 8).

. Class B four-finger slap identification appeared to be less accurate than Class A two-finger identification. This needs

further investigation as to the cause. Two possibilities are slap segmentation errors or fingerprint image quality.

After manually inspecting some of the errors and considering the ten finger IDFlat and plain-to-plain results, it

would appear that image quality may have been the largest contributing factor.

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I2 D2 I1 Q1 Q2 D1 E2 V2 V1 L1 J2 L2 O2 G2 O1 E1 J1 G1 U1 S1 S2 U2 H1 H2 M2 M1 F1 F2 C2 C1 K1 K2 P1 P2 T1 T2

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Identification Flats

Left and Right Index

Left and Right Slap

Left Index

Left Slap

Right Index

Right Slap

Ten−Finger Plain−to−Plain

Ten−Finger Plain−to−Rolled

Ten−Finger Rolled−to−Rolled

Figure 72: Rank-sorted FNIR @ FPIR = 10−3for All Classes. Submissions “1” and “2” from round 3.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 83

12 FpVTE 2003 Comparison

FpVTE 2003 [17] was composed of three separate tests, the Large-Scale Test (LST), the Medium-Scale Test (MST), and the

Small-Scale Test (SST). SST and MST tested matching accuracy using individual fingerprints, all of which were images

from right index fingers. This contrasts with LST, which evaluated matching accuracy using sets of fingerprint images,

where each set includes one to ten finger positions collected from an individual subject at one time.

LST used 64 000 fingerprint sets from 25 000 subjects. These fingerprint sets comprised multiple test sets with varying

combinations of one, two, four, eight, and ten fingers. MST used 10 000 right index fingers and SST used a subset of 1 000

right index fingers.

A significant difference between FpVTE 2012 and FpVTE 2003 testing procedures was that FpVTE 2003 required participants to match all subjects in the datasets against each other and return all 1-to-1 match scores. Therefore, while a direct

comparison of results from the two FpVTE evaluations is not possible, this section will look at some of the observations

from 2003 and note changes that have occurred in FpVTE 2012.

Looking at Figures 73 through 75 (focusing on the “Standard Partition” and “Average TAR”) , a notable observation is that

the accuracy gap in 2003 between the most accurate and least accurate systems was very significant. In current results,

there is still a measurable accuracy gap, but it doesn’t seem to be nearly as large.

In 2003, the accuracy results (as shown in Figure 76) indicated some difficulty measuring the accuracy difference when

using four-, eight-, and ten-finger datasets. While it was clear that more fingers produced higher accuracy, it was not clear

if ten fingers was significantly better than four fingers. The current FpVTE results used large enough datasets to allow a

more accurate measurement of four-, eight-, and ten-finger search sets. There was a noticeable improvement in matching

accuracy going from a four-finger search set to a ten-finger search set in FpVTE 2012.

Effects of fingerprint quality will be analyzed in a different FpVTE report to see if current technologies have improved

when using low quality fingerprint data.

Figure 73: FpVTE 2003 SST Results - Range of accuracy on single-finger flats (SST). These systems are sorted by accuracy

on the SST standard partition. Note that these results are reported at FAR = 10−3[17].

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
84 FPVTE – FINGERPRINT MATCHING

Figure 74: FpVTE 2003 MST Results - Range of accuracy across 7 MST partitions. These systems are sorted by accuracy on

the standard MST, which is simply the combination of the other partitions [17].

Figure 75: FpVTE 2003 LST Results - Range of accuracy over 27 operational LST partitions. The systems are sorted by their

average accuracy over the 27 partitions. Note that sorting by median accuracy would change the order for some systems

[17].

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 85 Figure 76: FpVTE 2003 LST Number of Finger Results - Effect of number of fingers and other variables in LST. The

y scale is the log of False Reject Rate

(FRR), which is 1 − TAR. Note that the single-finger searches (red) are clearly separated from the two-finger searches (green), but the four-, eight-, and

ten-finger searches are intermingled. At the test sizes used, accuracy of four-, eight-, and ten-finger searches is difficult to differentiate. The lines off ofthe top of the chart are for FRR = 0 (perfect results), which cannot be represented in log scale [17].

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
86 FPVTE – FINGERPRINT MATCHING

13 Lessons Learned for Large-Scale Testing

. Failure Feedback: One of the most difficult aspects of validation was providing useful feedback to participants when

failures occurred. The data used in FpVTE was sequestered operational data that could not be shared with participants. Some progress was made in FpVTE by allowing participants to write text-only logs, from their submission

executed at NIST, that could then be returned for analysis. NIST reviewed all logs to ensure the logs did not include

information related to the imagery or the NIST internal computing environment. Enhancements could be made to

the FpVTE API to allow the FpVTE test driver to toggle logging on and off, preventing participants from submitting

a separate logging build while maintaining the speed of not logging under normal use.

. Two-Stage Matching Data Transfer: The FpVTE API specifies a 4 GB RAM disk to allow submissions to write data

during the first stage of identification that could be referred to during the second stage. The intent was for all

processes running on a compute node to share the same 4 GB RAM disk. As NIST did not say how many processes

would be run in parallel, it created problems for submissions that wrote a large amount of data per process during

the first stage of identification. Without increasing the RAM disk size, NIST was forced to run fewer processes on

each compute node to avoid overfilling the RAM disk, which increased the evaluation time and wasted compute

node resources. For instance, a compute node that would typically run twenty stage one identification processes

might be limited to running just two or three. Future evaluations should better define the expected RAM disk usage,

a minimum number of concurrent processes, and other requirements needed to safely and effectively run multiple

searches in parallel.

. Shared Memory: A key feature of the FpVTE API was that a large enrollment set could be loaded in memory and

shared among multiple processes in parallel. An important aspect in allowing this shared memory useage was

that the memory must remain static after initialization (see Section 5 for details). This caused problems for some

participants and took several validation iterations to correct.

. Additional Computational Statistics: The FpVTE test driver recorded the resident enrollment set size of identification stage one processes after returning from the identification stage one initialization method. It was expected

that participants would use this method to load the entire enrollment set partition into RAM. While this was a

fairly good indicator of RAM requirements, some submissions allocated significantly more memory during the core

identification stage one method, which in many cases required re-partitioning the enrollment set with an additional

compute node. Should FpVTE be repeated, it would be more fair to record additional computational statistics, such

as peak RAM consumption over the execution time of the submission, since the RAM usage after initialization did

not completely represent the RAM resources required for some submissions to run.

. Timing Submissions: Keeping timing fair is a difficult task. The baseline of performing a timing test with only a

single FpVTE process running proved most successful at keeping timing fair for all participants. The timing test was

run against the full enrollment set with the assumption that using a smaller enrollment set would cause the search

times to decrease. In cases where any unusual results were noticed, the timing tests were repeated to verify that the

results remained consistent.

. Enrollment and Re-enrollment: Enrolling the full datasets (≈ 11.4 million total subjects across all three classes) was

not a trivial task. The original assumption was that this enrollment would only be performed for the first submission and not need to be repeated with later submissions. This was not the case and greatly increased the overall time

required to complete the evaluation. Any future evaluations of this magnitude should explore performing a “maximum size” template extraction up front, then allowing for adjustments during the finalization stage to only use the

minimum amount of information needed by the submissions. This could greatly reduce the need for re-enrollments.

Care would need to be taken when reporting the “size” of the enrollment templates for each submission.

. Enrollment Size — Disk vs. RAM: Another failed assumption was that reporting the size of the template at extraction would be a good indicator of how much RAM the enrollment set required (i.e., the Actual RAM and Reported

RAM columns from the tables Section 9 should be relatively close). For most submissions, this was true. Other

submissions either compressed the templates and required more memory than it appeared they would need (at least

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 87

one participant warned NIST that this would be the case) or they required less storage than the template sizes indicated they would need (again, at least one participant sent a warning about this issue). While the FpVTE API tried

to prevent this by asking for both memory usage in RAM and on disk, there was confusion among the participants

on what values, if any, to return. For example, many participants were confused on how to report memory usage of

slap images—the participant would segment the fingers and return a single template, but report back four separate

RAM usage values. Future evaluations will need to provide better guidance on this issue.

. Consolidations of Nonmate Searches: A large amount of unexpected time was spent performing consolidations on

the “back-end” of the searches. There proved to be a lot more consolidations to examine than originally expected. It

took two to three months to clean these up before meaningful results could be produced. A significant improvement

to this issue was the decision to flip nonmate search images, as discussed in Subsection 6.5.

. Operational Sequestered Data: Participants were able to learn things about their specific submissions even though

they may not have been one of the top performers. Some participants shared with NIST that they were grateful to test

on the large sample of sequestered operational data to which they might not otherwise have access. They may not

have had the best performance, but they were looking to learn about limitations with their submissions and make

improvements, which was one of stated goals of FpVTE. This should continue to help advance fingerprint matching

technologies and support the NIST mission of, “promoting U.S. innovation and industrial competitiveness”.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
88 FPVTE – FINGERPRINT MATCHING

14 Way Forward

NIST plans to publish further research and analysis in addition to this initial results report, including:

. running larger search sets (300 000 nonmates and 50 000 mates) so that DET curves can show accuracy with FPIR

rates below 10−3;

. performing failure analysis in an attempt to determine if there are common failures among submissions and what

causes those failures. Some things to examine during failure analysis include image quality, segmentation errors,

gender differences, and consolidation errors;

. performing analysis of results based on NFIQ values for the datasets;

. looking at accuracy of subgroups of metadata, such as male versus female.

. performing further analysis and testing to determine possible causes for four-finger IDFlat slap images being less

accurate than two-index finger single-capture images;

If FpVTE were to be repeated, it might be useful to concentrate more on throughput versus accuracy. For instance, rather

than set a single maximum search time of 90 seconds, the evaluation could have several search time maximums in an effort

to see how different search times impact matching accuracy. It was clear during this evaluation that some participants have

finer-grained control over the speed in which searches were performed. A speed-vs-accuracy track/competition would

be useful.

14.1 Related Testing

14.1.1 Forensic Palmprint

As data becomes available, the protocols from this evaluation could be applied to perform an evaluation for latent palmprint matching.

14.1.2 Mobile Data

NIST has performed some testing with simulated mobile data, but future evaluations should look at using operational

mobile data in the search sets to see how it impacts performance of matching algorithms.

14.1.3 Cross-Comparison of Modalities

Additional testing will compare the performance of fingerprint, face, and iris matching algorithms, in which all use a

search set of 1.6 million subjects. While the datasets will be captured from different sources and subjects, this will be one

of the first steps in comparing different modalities on similar sample sizes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 89

References

[1] CHAMBERS, J., CLEVELAND, W., KLEINER, B., AND TUKEY, P. Graphical Methods for Data Analysis. Wadsworth

Brooks/Cole, 1983. 198

[2] CRIMINAL JUSTICE INFORMATION SERVICES DIVISION — FEDERAL BUREAU OF INVESTIGATION. IAFIS-IC-0110

(V3.1) WSQ Gray-scale Fingerprint Image Compression Specification, 2010. 6

[3] GROTHER, P., MICHAELS, R., AND PHILLIPS, P. J. Face Recognition Vendor Test 2002 Performance Metrics. In Audioand Video-Based Biometric Person Authentication: 4th International Conference, AVBPA 2003, Guildford, UK, June 9–11, 2003

Proceedings (June 2003), J. Kittler and M. S. Nixon, Eds., vol. 2688, Springer Berlin Heidelberg, pp. 937–945. 1

[4] GROTHER, P., QUINN, G., MATEY, J., NGAN, M., SALAMON, W., FIUMARA, G., AND WATSON, C. Iris Exchange III.

NIST Interagency Report 7836 (2012). 18

[5] IMAGE GROUP — NIST. NIST Biometric Evaluations Website. http://www.nist.gov/itl/iad/ig/biometric_

evaluations.cfm. 3

[6] INTERNATIONAL COMMITTEE FOR INFORMATION TECHNOLOGY STANDARDS. American National Standard for Information Technology - Finger Minutiae Format for Data Interchange, ANSI/INCITS 378-2004, 2004. 3

[7] ISO/IEC JTC 1 SC 37. Information technology – Vocabulary – Part 37: Biometrics. http://standards.iso.org/

ittf/PubliclyAvailableStandards/c055194_ISOIEC_2382-37_2012.zip, 2012. 1

[8] KOMARINSKI, P. Automated Fingerprint Identification Systems (AFIS), 1st ed. Elsevier, 2004. ISBN 9780080475981. 19

[9] MARTIN, A. F., DODDINGTON, G. R., TERRI KAMM, M. O., AND PRZYBOCKI, M. A. The DET curve in assessment

of detection task performance, 1997. 18

[10] OPEN MPI PROJECT. Open MPI: Open Source High Performance Computing. http://www.open-mpi.org/, 2014.

[Online; accessed 22 October 2014]. 11

[11] SALAMON, W., AND FIUMARA, G. Biometric Evaluation Framework. http://www.nist.gov/itl/iad/ig/framework.

cfm, 2014. [Online; accessed 28 August 2014]. 11

[12] TABASSI, E., AND WILSON, C. L. A novel approach to fingerprint image quality. In Image Processing, 2005. ICIP 2005.

IEEE International Conference on (Sept 2005), vol. 2, pp. II–37–40. 6

[13] TABASSI, E., WILSON, C. L., AND WATSON, C. I. Fingerprint Image Quality. NIST Interagency Report 7151 (2004). 6

[14] WATSON, C., GARRIS, M. D., TABASSI, E., WILSON, C. L., MCCABE, R. M., JANET, S., AND KO, K. User’s Guide to

Export Controlled Distribution of NIST Biometric Image Software (NBIS-EC). NIST Interagency Report 7391 (2007). 6

[15] WATSON, C., SALAMON, W., AND FIUMARA, G. Fingerprint Vendor Technology Evaluation Implementer’s Guide. National Institute of Standards and Technology, http://nigos.nist.gov:8080/evaluations/fpvte2012/FPVTE2012_API_

Plan_full_060712.pdf, July 2012. xvi, 1, 61

[16] WAYMAN, J., JAIN, A., MALTONI, D., AND MAI, D. Biometric Systems: Technology, Design and Performance

Evaluation, 2005. ISBN 1852335963. 19

[17] WILSON, C., HICKLIN, R. A., BONE, M., KORVES, H., GROTHER, P., ULERY, B., MICHEALS, R., ZOEPFL, M., OTTO,

S., AND WATSON, C. Fingerprint Vendor Technology Evaluation 2003. NIST Interagency Report 7123 (2004). 82, 83,

84, 85

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
90 FPVTE – FINGERPRINT MATCHING

A Individual Participant FNIR Plots

This appendix contains a full size DET curve for every participant in FpVTE. The reader is reminded that enrollment set

sizes were 100 000 subjects for single index fingers, 1.6 million subjects for two index fingers, 3 million subjects for IDFlats,

and 5 million for ten-finger rolled and plain impressions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 91

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 77: DET for Participant C — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
92 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 78: DET for Participant D — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 93

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 79: DET for Participant E — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
94 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 80: DET for Participant F — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 95

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 81: DET for Participant G — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
96 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 82: DET for Participant H — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 97

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 83: DET for Participant I — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
98 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 84: DET for Participant J — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 99

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)

Left and Right Index (1)Left Index (2)

Right Index (2)Left and Right Index (2)

Figure 85: DET for Participant K — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
100 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 86: DET for Participant L — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 101

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 87: DET for Participant M — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
102 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 88: DET for Participant O — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 103

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)

Left and Right Index (1)Left Index (2)

Right Index (2)Left and Right Index (2)

Figure 89: DET for Participant P — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
104 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 90: DET for Participant Q — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 105

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 91: DET for Participant S — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
106 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Right Index (1)Left Index (1)

Left Index (2)Left and Right Index (1)

Left and Right Index (2)Right Index (2)

Figure 92: DET for Participant T — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 107

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Index (1)Right Index (1)Left and Right Index (1)Right Slap (1)Left Slap (1)

Left and Right Slap (1)Identification Flats (1)Ten−Finger Plain−to−Plain (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Rolled (1)

Left Index (2)Right Index (2)Left and Right Index (2)Right Slap (2)Left Slap (2)

Left and Right Slap (2)Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Rolled (2) Figure 93: DET for Participant U — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
108 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005 0.0010 0.0020 0.0050 0.0100 0.0200 0.0500 0.1000 0.2000 0.5000

Left Slap (1)Right Slap (1)Left and Right Index (1)Right Index (1)Left Index (1)

Ten−Finger Plain−to−Rolled (1)Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1)Left and Right Slap (1)

Left Slap (2)Right Slap (2)Left and Right Index (2)Right Index (2)Left Index (2)

Ten−Finger Plain−to−Rolled (2)Ten−Finger Rolled−to−Rolled (2)Ten−Finger Plain−to−Plain (2)Identification Flats (2)Left and Right Slap (2)

Figure 94: DET for Participant V — All fingers with maximum enrollment sets for each class.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 109

B Combined Class DETs and CMCs

This appendix contains DET and CMC curves for all classes and participants grouped together. There is one grouping for

the participant’s first submission and another for their second submission. The submissions are split for visibility only—

“first” and “second” submissions do not imply any sort of logical grouping. The reader is reminded that enrollment set

sizes were 100 000 subjects for single index fingers, 1.6 million subjects for two index fingers, 3 million subjects for IDFlats,

and 5 million for ten-finger rolled and plain impressions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
110 FPVTE – FINGERPRINT MATCHING

False Positive Identification Rate

False Negative Identification Rate

0.00050.00100.00200.00500.01000.02000.05000.10000.20000.5000

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

P Q

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

S T

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

U V

I J K L M O 0.0005

0.00100.00200.00500.01000.02000.05000.10000.20000.5000

C D E F G H

Left and Right Index (1)Right Index (1)Left Index (1)

Left and Right Slap (1)Left Slap (1)Right Slap (1)

Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1) Ten−Finger Plain−to−Rolled (1)

Figure 95: DETs from the first submission for all participants in all classes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 111

False Positive Identification Rate

False Negative Identification Rate

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

P Q

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

S T

0.0005

0.0010

0.0020

0.0050

0.0100

0.0200

0.0500

0.1000

0.2000

0.5000

U V

I J K L M O

0.50000.20000.10000.05000.02000.01000.00500.00200.00100.0005

C D E F G H

Left Index (2)Right Index (2)Left and Right Index (2)

Right Slap (2)Left Slap (2)Left and Right Slap (2)

Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)

Ten−Finger Plain−to−Rolled (2) Figure 96: DETs from the second submission for all participants in all classes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
112 FPVTE – FINGERPRINT MATCHING

Rank

Miss Rate

0.00100.00200.00500.01000.02000.05000.10000.2000

5 10 15

P Q

5 10 15

S T

5 10 15

U V

I J K L M O

0.00100.00200.00500.01000.02000.05000.10000.2000 C D E F G H

Left and Right Index (1)Right Index (1)Left Index (1)

Left and Right Slap (1)Left Slap (1)Right Slap (1)

Ten−Finger Rolled−to−Rolled (1)Ten−Finger Plain−to−Plain (1)Identification Flats (1) Ten−Finger Plain−to−Rolled (1)

Figure 97: CMCs from the first submission for all participants in all classes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 113

Rank

Miss Rate

0.20000.10000.05000.02000.01000.00500.00200.0010

5 10 15

P Q

5 10 15

S T

5 10 15

U V

I J K L M O

0.20000.10000.05000.02000.01000.00500.00200.0010

C D E F G H

Left Index (2)Right Index (2)Left and Right Index (2)

Right Slap (2)Left Slap (2)Left and Right Slap (2)

Identification Flats (2)Ten−Finger Plain−to−Plain (2)Ten−Finger Rolled−to−Rolled (2)

Ten−Finger Plain−to−Rolled (2) Figure 98: CMCs from the second submission for all participants in all classes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
114 FPVTE – FINGERPRINT MATCHING

C Accuracy Time Tradeoff Detailed Tables with Median Values

In order to reduce the number of tables in the main body of the report (Section 8), this appendix contains tables that show

the search times for each stage of identification, for both a single process and ten processes.

The tables in this appendix report median times. For readers interested in mean times, please refer to Appendix D.

Class A results are in Tables 24 through 29, Class B results are in Tables 30 through 33, and Class C results are in Tables 34

through 36.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 115

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 1 0.26 1 0.26 1 — 1 — 1 0.26 1 0.26

C

2 6 0.76 6 0.72 1 — 1 — 6 0.76 6 0.72

D 1 17 3.89 16 3.90 28 3.54 27 1.62 20 7.32 18 5.56

1 3 0.35 3 0.38 1 — 1 — 3 0.35 3 0.38

E

2 30 16.90 29 16.93 1 — 1 — 30 16.90 28 16.931 12 2.49 12 2.40 1 — 1 — 11 2.49 11 2.40

F

2 15 3.56 14 3.52 1 — 1 — 14 3.56 13 3.52

G 1 23 9.74 24 10.10 1 — 1 — 21 9.74 23 10.10

1 16 3.61 17 4.54 1 — 1 — 15 3.61 15 4.54

H

2 19 4.13 18 5.09 1 — 1 — 17 4.13 16 5.09

I 1 24 9.94 25 10.36 1 — 1 — 22 9.94 24 10.36

1 4 0.54 4 0.56 1 — 1 — 4 0.54 4 0.56

J

2 7 1.25 8 1.28 1 — 1 — 7 1.25 7 1.281 26 10.44 27 11.21 1 — 1 — 25 10.44 26 11.21

K

2 25 10.32 26 11.18 1 — 1 — 23 10.32 25 11.181 2 0.28 2 0.27 1 — 1 — 2 0.29 2 0.27

L

2 13 3.32 15 3.79 1 — 1 — 12 3.32 14 3.791 11 1.84 11 1.78 1 — 1 — 10 1.84 10 1.78

M

2 27 10.70 23 9.58 1 — 1 — 26 10.70 22 9.581 5 0.62 5 0.61 1 — 1 — 5 0.62 5 0.61

O

2 10 1.56 10 1.62 1 — 1 — 9 1.56 9 1.621 8 1.32 9 1.36 1 — 1 — 8 1.32 8 1.36

P

2 14 3.33 13 3.20 1 — 1 — 13 3.33 12 3.201 28 11.25 28 11.61 29 4.48 29 1.79 28 15.70 27 13.44

Q

2 22 7.67 22 7.73 27 2.64 28 1.70 24 10.43 21 9.45

S 1 29 16.86 30 17.66 1 — 1 — 29 16.86 29 17.66

1 18 3.99 19 5.43 1 — 1 — 16 3.99 17 5.44

T

2 20 5.97 21 7.15 1 — 1 — 18 5.97 20 7.15

U 1 9 1.41 7 1.14 30 12.96 30 17.63 27 14.42 30 18.76

V 1 21 6.01 20 5.81 1 — 1 — 19 6.01 19 5.81

FNIR @ FPIR

= 10

−3

24 0.133525 0.1337

1 0.0197

12 0.074511 0.072320 0.111118 0.108219 0.108926 0.157627 0.1607

5 0.0257

14 0.078610 0.071217 0.088316 0.0875

8 0.06256 0.0351

29 0.299528 0.292115 0.081813 0.076623 0.130822 0.1272

2 0.02223 0.02267 0.0571

30 NA

9 0.0685

21 0.1218

4 0.0253

Table 24: Tabulation of median identification time results for Class A — Left Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer of this page.

Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with

Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported inseconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
116 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

D 2 1 18.19 1 18.37 6 22.44 6 3.14 3 41.84 1 21.60

G 2 5 54.03 5 56.40 1 — 1 — 5 54.03 5 56.40

I 2 3 40.99 3 43.35 1 — 1 — 2 40.99 3 43.35

S 2 4 44.66 4 47.82 1 — 1 — 4 44.66 4 47.82

U 2 2 23.74 2 39.38 5 0.41 5 0.35 1 24.16 2 39.70

V 2 6 65.35 6 64.02 1 — 1 — 6 65.35 6 64.02

FNIR @ FPIR

= 10

−3

1 0.01975 0.10863 0.02784 0.06506 0.11782 0.0252

Table 25: Tabulation of median identification time results for Class A — Left Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found on thefooter of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined

in Section 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations

are reported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of

a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right ofthis table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 117

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 1 0.24 1 0.24 1 — 1 — 1 0.24 1 0.24

C

2 6 0.69 6 0.68 1 — 1 — 6 0.69 6 0.68

D 1 18 3.77 15 3.68 29 3.69 27 1.56 20 7.46 17 5.27

1 3 0.32 3 0.35 1 — 1 — 3 0.32 3 0.35

E

2 29 16.27 29 16.58 1 — 1 — 29 16.27 29 16.581 12 2.38 12 2.34 1 — 1 — 11 2.38 11 2.34

F

2 16 3.60 14 3.36 1 — 1 — 15 3.60 13 3.36

G 1 25 10.10 25 10.23 1 — 1 — 24 10.10 24 10.23

1 15 3.56 17 4.58 1 — 1 — 14 3.56 15 4.59

H

2 19 4.05 18 5.05 1 — 1 — 17 4.05 16 5.06

I 1 24 9.83 24 9.86 1 — 1 — 22 9.83 23 9.86

1 4 0.51 4 0.53 1 — 1 — 4 0.51 4 0.53

J

2 7 1.13 8 1.20 1 — 1 — 7 1.13 7 1.201 27 10.42 26 10.81 1 — 1 — 26 10.42 25 10.81

K

2 26 10.26 27 10.91 1 — 1 — 25 10.27 26 10.911 2 0.26 2 0.27 1 — 1 — 2 0.26 2 0.27

L

2 14 3.26 16 3.71 1 — 1 — 13 3.26 14 3.711 11 1.78 11 1.64 1 — 1 — 10 1.78 10 1.64

M

2 23 9.39 23 8.24 1 — 1 — 21 9.39 21 8.241 5 0.56 5 0.58 1 — 1 — 5 0.56 5 0.58

O

2 10 1.36 10 1.53 1 — 1 — 9 1.36 9 1.531 9 1.24 9 1.28 1 — 1 — 8 1.24 8 1.28

P

2 13 3.07 13 3.20 1 — 1 — 12 3.07 12 3.201 28 10.94 28 11.33 28 3.24 29 1.73 28 14.24 27 13.09

Q

2 22 7.39 22 7.57 27 2.53 28 1.67 23 9.98 22 9.24

S 1 30 16.55 30 16.75 1 — 1 — 30 16.55 30 16.75

1 17 3.73 20 5.66 1 — 1 — 16 3.73 19 5.66

T

2 21 5.86 21 7.21 1 — 1 — 19 5.87 20 7.21

U 1 8 1.24 7 1.01 30 9.19 30 14.92 27 10.76 28 15.85

V 1 20 5.60 19 5.61 1 — 1 — 18 5.60 18 5.61

FNIR @ FPIR

= 10

−3

24 0.113223 0.1124

1 0.0190

11 0.063010 0.062420 0.093318 0.090319 0.091026 0.123027 0.1249

3 0.0215

16 0.070812 0.064314 0.068215 0.0685

8 0.05056 0.0295

30 0.261529 0.252617 0.077613 0.067525 0.113322 0.1100

4 0.02182 0.02147 0.0442

28 0.1929

9 0.0562

21 0.0996

5 0.0223

Table 26: Tabulation of median identification time results for Class A — Right Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5,with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in

seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
118 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

D 2 1 17.43 1 17.53 6 11.53 6 3.02 2 28.64 1 20.55

G 2 5 59.55 5 58.30 1 — 1 — 5 59.55 5 58.30

I 2 3 40.35 3 42.08 1 — 1 — 3 40.35 3 42.08

S 2 4 46.05 4 45.80 1 — 1 — 4 46.05 4 45.80

U 2 2 19.74 2 34.25 5 0.33 5 0.32 1 20.10 2 34.54

V 2 6 61.24 6 60.53 1 — 1 — 6 61.24 6 60.53

FNIR @ FPIR

= 10

−3

1 0.01905 0.09092 0.02144 0.05036 0.10073 0.0222

Table 27: Tabulation of median identification time results for Class A — Right Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found on thefooter of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined

in Section 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations

are reported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of

a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right ofthis table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 119

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 1 2.08 1 2.23 1 — 1 — 1 2.08 1 2.23

C

2 4 6.35 3 6.54 1 — 1 — 4 6.35 3 6.54

G 1 3 5.22 4 6.62 1 — 1 — 3 5.22 4 6.62

I 1 8 17.87 8 18.87 1 — 1 — 8 17.87 8 18.87

J 1 6 13.64 6 14.42 1 — 1 — 6 13.64 6 14.42

K 1 9 18.01 9 18.95 1 — 1 — 9 18.01 9 18.95

L 1 2 2.19 2 5.05 1 — 1 — 2 2.19 2 5.05

O 1 7 14.46 7 15.50 1 — 1 — 7 14.46 7 15.50

V 1 5 9.29 5 9.45 1 — 1 — 5 9.29 5 9.45

FNIR @ FPIR

= 10

−3

7 0.03688 0.03749 0.05152 0.00583 0.01436 0.03604 0.01465 0.02291 0.0034

Table 28: Tabulation of median identification time results for Class A — Left and Right Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer ofthis page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5,

with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported inseconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
120 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

1 2 19.27 2 19.30 24 52.34 24 19.23 15 70.99 6 37.59

D

2 21 164.19 21 169.73 26 68.09 23 7.29 23 237.43 21 182.691 1 16.35 1 18.25 1 — 1 — 1 16.35 1 18.25

E

2 27 518.11 27 512.28 1 — 1 — 27 518.11 27 512.281 14 60.66 11 57.10 1 — 1 — 13 60.66 11 57.10

F

2 16 73.95 13 68.04 1 — 1 — 16 73.95 13 68.04

G 2 23 221.16 23 233.70 1 — 1 — 22 221.16 22 233.71

1 10 36.71 8 39.83 1 — 1 — 8 36.71 7 39.83

H

2 13 52.25 10 54.92 1 — 1 — 12 52.25 10 54.92

I 2 25 338.88 24 377.30 1 — 1 — 25 338.88 24 377.31

J 2 9 33.35 7 36.28 1 — 1 — 7 33.35 5 36.28

K 2 8 32.93 6 33.62 1 — 1 — 6 32.93 4 33.62

L 2 4 23.42 14 69.95 1 — 1 — 3 23.42 14 69.95

1 7 31.44 5 30.23 1 — 1 — 5 31.44 3 30.23

M

2 22 171.24 22 169.90 1 — 1 — 20 171.24 19 169.90

O 2 12 43.53 9 46.77 1 — 1 — 10 43.53 8 46.77

1 15 63.65 12 62.81 1 — 1 — 14 63.65 12 62.81

P

2 18 101.16 17 105.73 1 — 1 — 17 101.16 16 105.731 20 153.61 20 160.28 25 57.36 26 80.55 21 212.69 23 242.28

Q

2 17 86.83 16 89.06 27 69.98 27 83.71 19 161.02 20 175.091 3 23.00 3 22.50 1 — 1 — 2 23.00 2 22.50

S

2 26 495.50 26 487.65 1 — 1 — 26 495.50 26 487.651 5 25.68 15 88.07 1 — 1 — 4 25.68 15 88.13

T

2 11 37.23 19 131.01 1 — 1 — 9 37.23 18 131.081 6 28.49 4 27.53 23 17.03 25 25.27 11 45.51 9 52.79

U

2 24 239.62 25 407.47 22 0.68 22 0.63 24 240.40 25 407.99

V 2 19 127.65 18 128.23 1 — 1 — 18 127.65 17 128.23

FNIR @ FPIR

= 10

−3

4 0.00304 0.0030

11 0.020710 0.020221 0.038622 0.041215 0.031124 0.068623 0.0684

4 0.00308 0.0143

14 0.0286

7 0.0072

26 NA25 NA12 0.021420 0.037016 0.0333

1 0.00271 0.0027

13 0.0281

9 0.0195

27 NA19 0.036617 0.033618 0.0358

3 0.0028

Table 29: Tabulation of median identification time results for Class A — Left and Right Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found

on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identificationdefined in Section 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median

durations are reported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to

the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the

right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 121

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 2 3.74 2 3.88 1 — 1 — 2 3.74 2 3.88

C

2 4 6.74 3 7.03 1 — 1 — 4 6.74 3 7.031 17 47.93 22 70.13 25 3.29 27 6.08 18 52.23 24 76.64

D

2 23 52.89 27 80.04 28 4.05 28 9.04 22 58.10 27 89.041 1 2.82 1 3.19 1 — 1 — 1 2.82 1 3.19

E

2 11 34.37 10 35.02 1 — 1 — 10 34.37 10 35.021 8 30.09 8 32.85 1 — 1 — 8 30.09 8 32.85

F

2 16 43.59 14 47.82 1 — 1 — 14 43.59 14 47.821 6 16.24 5 17.59 1 — 1 — 6 16.24 5 17.59

G

2 25 59.49 18 60.00 1 — 1 — 23 59.49 18 60.001 19 49.75 20 61.05 1 — 1 — 16 49.75 20 61.05

H

2 22 51.77 19 60.07 1 — 1 — 17 51.77 19 60.071 24 55.96 21 66.74 1 — 1 — 21 55.96 21 66.74

I

2 14 38.26 13 42.90 1 — 1 — 13 38.26 13 42.901 7 25.61 6 27.09 1 — 1 — 7 25.61 6 27.09

J

2 29 74.38 26 78.75 1 — 1 — 27 74.38 26 78.751 3 5.56 4 10.01 1 — 1 — 3 5.56 4 10.01

L

2 5 12.37 7 30.25 1 — 1 — 5 12.37 7 30.251 9 31.17 9 33.44 1 — 1 — 9 31.17 9 33.44

M

2 30 87.21 28 92.65 1 — 1 — 29 87.21 28 92.651 13 37.01 12 39.34 1 — 1 — 12 37.01 12 39.34

O

2 28 73.15 25 77.48 1 — 1 — 26 73.15 25 77.481 20 50.00 17 54.90 26 3.49 25 3.20 19 53.24 17 58.21

Q

2 21 50.78 16 53.59 27 3.55 26 3.32 20 54.02 16 57.021 26 71.69 23 74.67 1 — 1 — 24 71.69 22 74.67

S

2 27 71.77 24 74.84 1 — 1 — 25 71.77 23 74.841 10 33.57

— NA 30 47.07

— NA 28 80.03

— NA

U

2 15 42.79

— NA 29 45.59

— NA 30 89.07

— NA

1 12 36.07 11 36.78 1 — 1 — 11 36.07 11 36.78

V

2 18 47.97 15 50.36 1 — 1 — 15 47.97 15 50.37

FNIR @ FPIR

= 10

−3

22 0.065421 0.0647

6 0.01635 0.0142

13 0.0259

7 0.0187

29 0.168428 0.168118 0.037117 0.032523 0.099824 0.1008

4 0.01161 0.0094

15 0.028710 0.023616 0.028814 0.027630 0.173627 0.163412 0.025711 0.0254

2 0.00983 0.0099

25 0.108926 0.113320 0.050019 0.0461

9 0.01928 0.0190

Table 30: Tabulation of median identification time results for Class B — Left Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to

differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combinedsearch time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but were originallyrecorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could

not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIRvalues from Table 10 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
122 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 2 3.67 2 3.74 1 — 1 — 2 3.67 2 3.75

C

2 4 6.50 3 6.78 1 — 1 — 4 6.50 3 6.781 18 48.43 22 69.48 26 3.56 27 5.79 19 53.32 24 76.16

D

2 21 52.47 27 82.56 28 4.41 28 8.74 21 57.19 27 92.101 1 2.97 1 3.23 1 — 1 — 1 2.97 1 3.23

E

2 11 34.47 10 34.32 1 — 1 — 10 34.47 10 34.321 8 31.87 8 33.38 1 — 1 — 8 31.87 8 33.38

F

2 17 45.92 15 48.57 1 — 1 — 15 45.92 15 48.571 5 10.13 4 10.56 1 — 1 — 5 10.13 4 10.56

G

2 14 37.28 12 39.25 1 — 1 — 13 37.28 12 39.251 20 50.16 18 61.42 1 — 1 — 17 50.16 18 61.42

H

2 22 52.84 17 60.56 1 — 1 — 18 52.84 17 60.561 23 55.87 21 66.70 1 — 1 — 20 55.87 20 66.70

I

2 16 41.13 14 48.17 1 — 1 — 14 41.13 14 48.171 7 24.14 6 26.83 1 — 1 — 7 24.14 6 26.83

J

2 29 74.08 26 80.24 1 — 1 — 27 74.09 26 80.241 3 5.47 5 10.64 1 — 1 — 3 5.47 5 10.64

L

2 6 12.66 7 31.80 1 — 1 — 6 12.66 7 31.811 9 32.03 9 34.25 1 — 1 — 9 32.03 9 34.25

M

2 30 87.41 28 92.89 1 — 1 — 29 87.41 28 92.891 13 35.61 13 39.42 1 — 1 — 12 35.61 13 39.42

O

2 28 73.93 25 78.87 1 — 1 — 26 73.93 25 78.871 25 60.64 20 66.42 27 3.65 25 3.25 23 64.04 21 69.69

Q

2 24 58.39 19 63.34 25 3.54 26 3.30 22 61.94 19 66.611 26 70.54 23 74.64 1 — 1 — 24 70.54 22 74.64

S

2 27 70.84 24 75.02 1 — 1 — 25 70.84 23 75.021 10 34.38

— NA 30 54.61

— NA 30 89.26

— NA

U

2 15 40.66

— NA 29 40.70

— NA 28 80.11

— NA

1 12 35.43 11 37.08 1 — 1 — 11 35.43 11 37.08

V

2 19 48.51 16 50.24 1 — 1 — 16 48.51 16 50.24

FNIR @ FPIR

= 10

−3

24 0.040323 0.0392

6 0.00722 0.0052

13 0.0151

7 0.0083

29 0.122228 0.122018 0.021216 0.019825 0.064126 0.0647

5 0.00581 0.0045

14 0.015610 0.012615 0.016717 0.020230 0.125927 0.115512 0.014211 0.0132

3 0.00573 0.0057

21 0.036922 0.038119 0.026620 0.0273

8 0.01069 0.0110

Table 31: Tabulation of median identification time results for Class B — Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used todifferentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combined

search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but were originallyrecorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could

not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIRvalues from Table 11 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 123

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 3 6.40 3 6.63 1 — 1 — 3 6.40 3 6.63

C

2 5 10.70 4 11.10 1 — 1 — 5 10.70 4 11.101 22 59.32 27 104.95 27 1.34 27 2.40 20 61.24 27 108.01

D

2 23 60.79 28 106.49 28 2.28 28 4.43 21 63.05 28 111.351 2 6.12 2 6.09 1 — 1 — 2 6.12 2 6.09

E

2 11 33.09 10 35.61 1 — 1 — 10 33.09 10 35.611 9 27.27 8 30.15 1 — 1 — 9 27.27 8 30.15

F

2 13 36.36 11 40.13 1 — 1 — 12 36.36 11 40.131 1 3.89 1 4.17 1 — 1 — 1 3.89 1 4.17

G

2 12 34.55 9 34.99 1 — 1 — 11 34.55 9 34.991 27 70.38 26 86.18 1 — 1 — 25 70.38 26 86.18

H

2 28 73.06 24 85.16 1 — 1 — 26 73.06 24 85.161 14 37.19 14 42.38 1 — 1 — 13 37.19 14 42.38

I

2 19 46.13 16 54.07 1 — 1 — 17 46.13 16 54.071 7 26.15 6 28.45 1 — 1 — 7 26.15 6 28.45

J

2 26 69.28 22 74.42 1 — 1 — 24 69.28 22 74.421 4 10.47 5 22.48 1 — 1 — 4 10.48 5 22.48

L

2 6 20.78 19 63.81 1 — 1 — 6 20.78 19 63.821 8 27.15 7 30.00 1 — 1 — 8 27.15 7 30.01

M

2 18 45.91 15 51.07 1 — 1 — 16 45.91 15 51.071 15 38.34 13 41.51 1 — 1 — 14 38.34 13 41.51

O

2 25 68.46 21 73.17 1 — 1 — 23 68.46 21 73.171 24 63.79 20 69.86 26 1.07 26 0.79 22 65.02 20 70.73

Q

2 20 52.39 18 57.81 25 1.05 25 0.76 19 53.40 18 58.571 30 83.33 25 85.38 1 — 1 — 29 83.33 25 85.38

S

2 29 82.13 23 85.11 1 — 1 — 27 82.13 23 85.111 10 29.82

— NA 30 53.54

— NA 30 83.62

— NA

U

2 16 38.83

— NA 29 43.88

— NA 28 82.40

— NA

1 17 38.93 12 41.09 1 — 1 — 15 38.93 12 41.09

V

2 21 52.79 17 55.29 1 — 1 — 18 52.80 17 55.29

FNIR @ FPIR

= 10

−3

30 NA29 NA

6 0.00315 0.0024

15 0.006310 0.004928 0.091026 0.090118 0.010617 0.008423 0.034924 0.0361

3 0.00221 0.0015

16 0.0068

9 0.0047

12 0.005414 0.006227 0.090425 0.088213 0.005711 0.0051

2 0.00213 0.0022

21 0.016022 0.019020 0.013919 0.0124

7 0.00367 0.0036

Table 32: Tabulation of median identification time results for Class B — Left and Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier

used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the

combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,

the FNIR values from Table 12 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
124 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 3 7.92 3 7.99 1 — 1 — 3 7.92 3 7.99

C

2 4 10.21 4 10.62 1 — 1 — 4 10.21 4 10.621 19 44.48 22 79.06 25 0.86 27 1.33 17 45.15 22 80.68

D

2 20 45.79 23 83.76 26 1.43 28 2.30 18 46.70 24 86.691 2 6.76 2 7.23 1 — 1 — 2 6.76 2 7.24

E

2 17 43.61 13 48.02 1 — 1 — 15 43.61 13 48.021 13 37.56 11 40.93 1 — 1 — 12 37.56 11 40.93

F

2 22 49.34 17 54.18 1 — 1 — 20 49.34 17 54.181 1 4.26 1 4.52 1 — 1 — 1 4.26 1 4.52

G

2 6 16.26 5 14.99 1 — 1 — 6 16.26 5 14.991 27 82.66 27 97.33 1 — 1 — 26 82.66 27 97.33

H

2 28 86.56 28 98.56 1 — 1 — 27 86.56 28 98.561 7 19.07 6 21.52 1 — 1 — 7 19.07 6 21.52

I

2 18 43.86 16 54.10 1 — 1 — 16 43.86 16 54.101 8 25.38 7 26.88 1 — 1 — 8 25.38 7 26.88

J

2 24 60.13 19 64.19 1 — 1 — 22 60.13 19 64.191 5 14.49 8 34.38 1 — 1 — 5 14.50 8 34.39

L

2 9 28.59 24 86.01 1 — 1 — 9 28.59 23 86.021 14 38.87 12 42.78 1 — 1 — 13 38.87 12 42.78

M

2 26 65.91 20 72.75 1 — 1 — 23 65.91 20 72.751 12 35.64 10 38.07 1 — 1 — 11 35.64 10 38.07

O

2 23 60.02 18 63.40 1 — 1 — 21 60.02 18 63.401 16 41.50 14 49.75 28 1.48 25 1.00 14 42.92 14 50.75

Q

2 25 64.62 21 78.68 27 1.48 26 1.02 24 66.01 21 79.701 29 87.60 25 90.62 1 — 1 — 29 87.60 25 90.62

S

2 30 88.46 26 92.93 1 — 1 — 30 88.46 26 92.931 10 29.91

— NA 30 57.06

— NA 28 86.60

— NA

U

2 15 41.20

— NA 29 35.79

— NA 25 75.28

— NA

1 11 34.96 9 37.51 1 — 1 — 10 34.96 9 37.51

V

2 21 49.30 15 51.13 1 — 1 — 19 49.30 15 51.13

FNIR @ FPIR

= 10

−3

30 NA29 NA

6 0.00202 0.0012

16 0.0043

7 0.0024

27 0.059127 0.059118 0.006214 0.004023 0.020324 0.0204

2 0.00121 0.0009

17 0.004911 0.003310 0.003111 0.003326 0.054325 0.051515 0.004113 0.0035

2 0.00122 0.0012

20 0.010821 0.013619 0.009922 0.0141

9 0.00277 0.0024

Table 33: Tabulation of median identification time results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifierused to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the

combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,the FNIR values from Table 13 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 125

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 4 18.30 4 19.19 1 — 1 — 4 18.30 4 19.19

C

2 5 18.38 3 19.05 1 — 1 — 5 18.38 3 19.051 26 72.26 28 141.45 25 1.36 27 1.85 25 73.93 28 143.53

D

2 25 71.36 27 137.48 26 1.63 28 2.10 26 74.36 27 140.571 2 12.77 2 13.68 1 — 1 — 2 12.77 2 13.68

E

2 19 52.91 15 54.82 1 — 1 — 17 52.91 15 54.821 17 51.69 14 51.98 1 — 1 — 15 51.69 14 51.98

F

2 20 60.86 16 61.46 1 — 1 — 18 60.86 16 61.461 1 7.71 1 8.79 1 — 1 — 1 7.71 1 8.79

G

2 7 23.69 5 30.21 1 — 1 — 7 23.69 5 30.211 23 68.07 22 78.40 1 — 1 — 21 68.07 22 78.40

H

2 22 65.36 20 73.09 1 — 1 — 20 65.36 19 73.101 18 52.41 17 63.47 1 — 1 — 16 52.41 17 63.47

I

2 10 38.28 9 40.63 1 — 1 — 10 38.28 9 40.631 12 43.57 12 47.12 1 — 1 — 12 43.57 12 47.12

J

2 28 77.75 24 84.93 1 — 1 — 28 77.75 24 84.931 3 17.50 8 39.57 1 — 1 — 3 17.51 7 39.58

L

2 6 20.73 19 66.62 1 — 1 — 6 23.53 21 74.431 11 43.37 10 43.13 1 — 1 — 11 43.37 10 43.13

M

2 13 46.70 11 46.86 1 — 1 — 13 46.70 11 46.861 24 68.54 21 74.17 1 — 1 — 23 68.54 20 74.17

O

2 27 73.41 23 83.44 1 — 1 — 24 73.41 23 83.441 9 35.17 7 38.39 27 1.63 26 1.51 9 36.86 8 39.96

Q

2 8 33.71 6 35.06 28 1.70 25 1.36 8 35.35 6 36.231 29 86.56 25 95.71 1 — 1 — 29 86.56 25 95.71

S

2 30 91.74 26 98.32 1 — 1 — 30 91.74 26 98.321 15 47.96

— NA 30 26.89

— NA 27 74.94

— NA

U

2 16 51.07

— NA 29 17.32

— NA 22 68.30

— NA

1 14 47.02 13 48.95 1 — 1 — 14 47.02 13 48.95

V

2 21 62.26 18 65.76 1 — 1 — 19 62.26 18 65.76

FNIR @ FPIR

= 10

−3

30 NA24 0.0711

6 0.00152 0.0011

14 0.008813 0.004825 0.073425 0.073423 0.036820 0.027620 0.027619 0.0275

4 0.00131 0.0010

12 0.004710 0.002716 0.010215 0.009528 0.093427 0.0826

9 0.0025

10 0.0027

2 0.00114 0.0013

22 0.031129 0.168018 0.016317 0.0155

7 0.00247 0.0024

Table 34: Tabulation of median identification time results for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,

the FNIR values from Table 14 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
126 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 5 20.15 4 21.10 1 — 1 — 4 20.15 4 21.10

C

2 6 21.97 5 22.27 1 — 1 — 6 21.97 5 22.271 19 56.37 25 81.93 28 2.42 25 1.40 17 58.92 25 83.71

D

2 28 73.52 28 126.56 25 1.86 26 1.79 27 74.97 28 128.861 2 8.63 2 9.82 1 — 1 — 2 8.63 2 9.82

E

2 11 42.73 9 44.54 1 — 1 — 11 42.73 9 44.541 18 55.79 14 59.83 1 — 1 — 16 55.79 13 59.83

F

2 22 68.20 20 72.22 1 — 1 — 20 68.20 19 72.221 1 7.78 1 7.67 1 — 1 — 1 7.78 1 7.67

G

2 3 19.46 3 18.47 1 — 1 — 3 19.46 3 18.471 30 84.51 26 94.60 1 — 1 — 30 84.51 26 94.60

H

2 29 84.50 27 95.02 1 — 1 — 29 84.50 27 95.021 17 54.56 12 56.96 1 — 1 — 15 54.56 12 56.96

I

2 7 30.82 6 30.34 1 — 1 — 7 30.82 6 30.341 9 33.02 7 36.39 1 — 1 — 9 33.02 7 36.39

J

2 21 67.98 23 75.20 1 — 1 — 19 67.98 23 75.201 8 31.68 16 64.80 1 — 1 — 8 31.68 15 64.81

L

2 4 19.64 13 57.57 1 — 1 — 5 20.25 16 66.391 12 48.08 10 50.93 1 — 1 — 12 48.08 10 50.93

M

2 14 48.80 11 52.10 1 — 1 — 13 48.80 11 52.101 16 54.41 15 60.77 1 — 1 — 14 54.42 14 60.77

O

2 23 69.30 22 75.08 1 — 1 — 21 69.30 22 75.081 27 72.31 19 71.41 26 2.22 27 2.49 26 74.40 21 73.83

Q

2 26 72.05 17 67.31 27 2.27 28 2.51 25 74.22 18 69.951 24 69.71 24 77.04 1 — 1 — 22 69.71 24 77.04

S

2 25 70.77 21 72.56 1 — 1 — 23 70.77 20 72.561 13 48.12

— NA 30 34.90

— NA 28 82.61

— NA

U

2 15 52.49

— NA 29 21.02

— NA 24 72.48

— NA

1 10 40.74 8 42.25 1 — 1 — 10 40.74 8 42.25

V

2 20 65.07 18 67.32 1 — 1 — 18 65.07 17 67.33

FNIR @ FPIR

= 10

−3

16 0.009415 0.0085

4 0.00157 0.0018

18 0.010612 0.005025 0.053625 0.053624 0.044721 0.033320 0.020119 0.0199

1 0.00132 0.0014

13 0.0051

9 0.0033

17 0.009714 0.008328 0.078327 0.071611 0.0034

9 0.00335 0.00172 0.0014

29 0.086030 0.246223 0.035822 0.0351

5 0.00178 0.0019

Table 35: Tabulation of median identification time results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,the FNIR values from Table 15 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 127

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 6 33.68 5 35.85 1 — 1 — 6 33.68 5 35.85

C

2 8 34.85 6 36.23 1 — 1 — 8 34.85 6 36.231 12 41.16 20 69.81 25 0.60 25 0.58 13 41.67 20 70.49

D

2 18 56.17 28 109.60 26 1.04 26 1.16 16 57.36 28 110.641 1 8.99 1 9.76 1 — 1 — 1 8.99 1 9.76

E

2 7 34.06 4 35.00 1 — 1 — 7 34.06 4 35.001 21 58.57 16 60.32 1 — 1 — 19 58.57 15 60.32

F

2 23 61.87 17 62.74 1 — 1 — 21 61.87 17 62.741 2 16.78 2 20.00 1 — 1 — 2 16.78 2 20.00

G

2 4 22.14 3 26.40 1 — 1 — 4 22.14 3 26.401 24 64.83 25 77.97 1 — 1 — 22 64.83 25 77.97

H

2 25 65.74 21 73.89 1 — 1 — 23 65.74 21 73.891 16 52.47 19 67.66 1 — 1 — 15 52.47 19 67.66

I

2 13 41.48 10 45.62 1 — 1 — 12 41.48 10 45.621 11 38.41 9 41.85 1 — 1 — 9 38.41 9 41.85

J

2 27 67.88 24 75.26 1 — 1 — 25 67.88 24 75.261 5 27.47 14 58.46 1 — 1 — 5 27.47 13 58.47

L

2 3 18.30 11 48.54 1 — 1 — 3 20.18 16 60.351 19 57.63 13 58.09 1 — 1 — 17 57.63 12 58.09

M

2 20 57.91 15 59.52 1 — 1 — 18 57.91 14 59.521 22 59.05 18 64.96 1 — 1 — 20 59.05 18 64.96

O

2 26 66.80 23 74.41 1 — 1 — 24 66.80 23 74.411 9 36.83 8 39.07 28 1.91 27 1.70 11 39.76 8 40.80

Q

2 10 37.74 7 36.93 27 1.89 28 2.36 10 39.37 7 39.441 30 88.48 27 95.29 1 — 1 — 30 88.48 27 95.29

S

2 29 88.07 26 92.90 1 — 1 — 29 88.07 26 92.901 15 48.76

— NA 30 33.16

— NA 28 82.88

— NA

U

2 17 53.93

— NA 29 20.09

— NA 27 74.56

— NA

1 14 48.40 12 50.40 1 — 1 — 14 48.40 11 50.40

V

2 28 69.87 22 73.98 1 — 1 — 26 69.87 22 73.98

FNIR @ FPIR

= 10

−3

17 0.014918 0.0169

6 0.00283 0.0018

16 0.013712 0.005627 0.251427 0.251424 0.064923 0.052120 0.029119 0.0285

2 0.00141 0.0011

13 0.0071

7 0.0034

15 0.013614 0.012930 0.306727 0.251410 0.0041

8 0.00364 0.00205 0.0022

25 0.101726 0.236622 0.037821 0.029511 0.0052

9 0.0039

Table 36: Tabulation of median identification time results for Class C — Ten-Finger Plain-to-Rolled. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are median durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,

the FNIR values from Table 16 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
128 FPVTE – FINGERPRINT MATCHING

D Accuracy Time Tradeoff Detailed Tables with Mean Values

In order to reduce the number of tables in the main body of the report (Section 8), this appendix contains tables that show

the search times for each stage of identification, for both a single process and ten processes.

The tables in this appendix report mean times. For readers interested in median times, please refer to Appendix C.

Class A results are in Tables 37 through 42, Class B results are in Tables 43 through 46, and Class C results are in Tables 47

through 49.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 129

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 1 0.29 2 0.29 1 — 1 — 1 0.29 2 0.29

C

2 6 0.87 6 0.84 1 — 1 — 6 0.87 6 0.84

D 1 17 3.87 16 3.90 28 3.65 27 1.69 20 7.52 18 5.59

1 4 0.57 3 0.54 1 — 1 — 4 0.57 3 0.54

E

2 30 16.71 30 16.88 1 — 1 — 30 16.71 29 16.881 12 2.52 12 2.48 1 — 1 — 11 2.52 11 2.48

F

2 16 3.78 14 3.73 1 — 1 — 15 3.78 13 3.73

G 1 23 9.52 23 10.08 1 — 1 — 21 9.52 22 10.08

1 15 3.65 17 4.62 1 — 1 — 14 3.65 15 4.62

H

2 19 4.26 18 5.16 1 — 1 — 17 4.26 16 5.16

I 1 24 10.36 24 10.52 1 — 1 — 22 10.36 23 10.52

1 3 0.56 4 0.59 1 — 1 — 3 0.56 4 0.59

J

2 7 1.34 8 1.42 1 — 1 — 7 1.34 7 1.421 26 10.48 25 10.97 1 — 1 — 25 10.48 24 10.97

K

2 25 10.47 26 11.04 1 — 1 — 24 10.47 25 11.041 2 0.30 1 0.27 1 — 1 — 2 0.30 1 0.28

L

2 13 3.34 15 3.81 1 — 1 — 12 3.34 14 3.811 11 2.07 11 1.88 1 — 1 — 10 2.07 10 1.88

M

2 28 15.19 28 12.82 1 — 1 — 27 15.19 26 12.821 5 0.64 5 0.65 1 — 1 — 5 0.64 5 0.65

O

2 10 1.63 10 1.77 1 — 1 — 9 1.63 9 1.771 8 1.38 9 1.45 1 — 1 — 8 1.38 8 1.45

P

2 14 3.43 13 3.65 1 — 1 — 13 3.43 12 3.651 27 11.44 27 11.82 29 4.46 29 1.84 29 15.90 27 13.65

Q

2 22 7.71 22 7.83 27 2.71 28 1.74 23 10.42 21 9.57

S 1 29 15.37 29 15.90 1 — 1 — 28 15.37 28 15.90

1 18 4.18 19 5.47 1 — 1 — 16 4.18 17 5.47

T

2 20 5.96 21 6.72 1 — 1 — 18 5.96 20 6.72

U 1 9 1.45 7 1.18 30 13.27 30 18.84 26 14.72 30 20.02

V 1 21 6.22 20 6.08 1 — 1 — 19 6.22 19 6.08

FNIR @ FPIR

= 10

−3

24 0.133525 0.1337

1 0.0197

12 0.074511 0.072320 0.111118 0.108219 0.108926 0.157627 0.1607

5 0.0257

14 0.078610 0.071217 0.088316 0.0875

8 0.06256 0.0351

29 0.299528 0.292115 0.081813 0.076623 0.130822 0.1272

2 0.02223 0.02267 0.0571

30 NA

9 0.0685

21 0.1218

4 0.0253

Table 37: Tabulation of mean identification time results for Class A — Left Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer of this page.

Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total

indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, butwere originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides the value’s

column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
130 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

D 2 1 18.26 1 18.50 6 24.39 6 3.25 2 42.64 1 21.75

G 2 5 54.24 5 54.61 1 — 1 — 5 54.24 5 54.61

I 2 3 43.24 3 44.66 1 — 1 — 3 43.24 3 44.66

S 2 4 45.59 4 46.37 1 — 1 — 4 45.59 4 46.37

U 2 2 25.20 2 39.74 5 0.46 5 0.40 1 25.66 2 40.14

V 2 6 66.23 6 66.39 1 — 1 — 6 66.23 6 66.39

FNIR @ FPIR

= 10

−3

1 0.01975 0.10863 0.02784 0.06506 0.11782 0.0252

Table 38: Tabulation of mean identification time results for Class A — Left Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found on the footerof this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined inSection 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are

reported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right of this

table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 131

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 1 0.25 1 0.27 1 — 1 — 1 0.25 1 0.27

C

2 6 0.76 6 0.77 1 — 1 — 6 0.76 6 0.77

D 1 17 3.72 15 3.72 29 3.96 27 1.63 20 7.68 17 5.36

1 3 0.45 3 0.51 1 — 1 — 3 0.45 3 0.51

E

2 30 15.89 30 16.40 1 — 1 — 30 15.89 29 16.401 12 2.52 12 2.37 1 — 1 — 11 2.52 11 2.37

F

2 16 3.71 14 3.52 1 — 1 — 15 3.71 13 3.52

G 1 23 10.12 24 10.32 1 — 1 — 21 10.12 23 10.32

1 15 3.58 17 4.61 1 — 1 — 14 3.58 15 4.61

H

2 19 4.13 18 5.13 1 — 1 — 17 4.13 16 5.13

I 1 24 10.19 23 10.06 1 — 1 — 23 10.19 22 10.06

1 4 0.53 4 0.55 1 — 1 — 4 0.53 4 0.55

J

2 7 1.25 8 1.33 1 — 1 — 7 1.25 7 1.331 26 10.42 25 10.65 1 — 1 — 25 10.42 24 10.65

K

2 25 10.30 26 10.73 1 — 1 — 24 10.30 25 10.731 2 0.29 2 0.27 1 — 1 — 2 0.29 2 0.28

L

2 13 3.26 16 3.74 1 — 1 — 12 3.26 14 3.741 11 1.75 11 1.71 1 — 1 — 10 1.75 10 1.71

M

2 28 11.31 27 10.80 1 — 1 — 26 11.31 26 10.801 5 0.59 5 0.62 1 — 1 — 5 0.59 5 0.62

O

2 10 1.48 10 1.67 1 — 1 — 9 1.48 9 1.671 9 1.38 9 1.37 1 — 1 — 8 1.38 8 1.37

P

2 14 3.49 13 3.48 1 — 1 — 13 3.49 12 3.481 27 11.10 28 11.54 28 3.34 29 1.76 28 14.44 27 13.30

Q

2 22 7.43 22 7.66 27 2.71 28 1.72 22 10.15 21 9.37

S 1 29 15.08 29 15.12 1 — 1 — 29 15.08 28 15.12

1 18 3.82 20 6.12 1 — 1 — 16 3.82 19 6.12

T

2 20 5.64 21 6.83 1 — 1 — 18 5.64 20 6.83

U 1 8 1.30 7 1.06 30 10.72 30 16.39 27 12.02 30 17.45

V 1 21 5.95 19 5.88 1 — 1 — 19 5.95 18 5.88

FNIR @ FPIR

= 10

−3

24 0.113223 0.1124

1 0.0190

11 0.063010 0.062420 0.093318 0.090319 0.091026 0.123027 0.1249

3 0.0215

16 0.070812 0.064314 0.068215 0.0685

8 0.05056 0.0295

30 0.261529 0.252617 0.077613 0.067525 0.113322 0.1100

4 0.02182 0.02147 0.0442

28 0.1929

9 0.0562

21 0.0996

5 0.0223

Table 39: Tabulation of mean identification time results for Class A — Right Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer of this page.Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total

indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, butwere originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides the value’s

column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
132 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

D 2 1 17.36 1 17.75 6 11.90 6 3.15 2 29.26 1 20.89

G 2 5 57.88 5 56.87 1 — 1 — 5 57.88 5 56.87

I 2 3 41.60 3 43.20 1 — 1 — 3 41.60 3 43.20

S 2 4 43.56 4 44.05 1 — 1 — 4 43.56 4 44.05

U 2 2 21.97 2 35.01 5 0.42 5 0.39 1 22.39 2 35.39

V 2 6 64.47 6 63.54 1 — 1 — 6 64.47 6 63.54

FNIR @ FPIR

= 10

−3

1 0.01905 0.09092 0.02144 0.05036 0.10073 0.0222

Table 40: Tabulation of mean identification time results for Class A — Right Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found on the

footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification definedin Section 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are

reported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right of this

table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 133

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

seconds 20 <

1 2 2.39 1 2.66 1 — 1 — 2 2.39 1 2.66

C

2 4 6.34 3 6.55 1 — 1 — 4 6.34 3 6.55

G 1 3 6.27 4 7.48 1 — 1 — 3 6.27 4 7.48

I 1 9 18.92 9 20.61 1 — 1 — 9 18.92 9 20.61

J 1 6 14.00 6 15.16 1 — 1 — 6 14.00 6 15.16

K 1 8 18.32 8 18.82 1 — 1 — 8 18.32 8 18.82

L 1 1 2.20 2 5.03 1 — 1 — 1 2.20 2 5.03

O 1 7 15.34 7 16.58 1 — 1 — 7 15.34 7 16.58

V 1 5 9.50 5 9.59 1 — 1 — 5 9.50 5 9.59

FNIR @ FPIR

= 10

−3

7 0.03688 0.03749 0.05152 0.00583 0.01436 0.03604 0.01465 0.02291 0.0034

Table 41: Tabulation of mean identification time results for Class A — Left and Right Index — less than 20-second searches. Letter refers to the participant’s letter code found on the footer of

this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5,

with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in

seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
134 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

≥ 20 seconds

1 1 19.08 1 19.21 24 53.93 23 18.74 16 73.01 5 37.95

D

2 21 163.78 21 170.99 26 70.74 24 19.00 23 234.52 21 190.001 3 22.27 3 23.15 1 — 1 — 2 22.27 2 23.15

E

2 27 500.30 27 512.38 1 — 1 — 27 500.30 27 512.381 14 59.30 11 57.53 1 — 1 — 13 59.30 11 57.53

F

2 16 71.45 13 69.19 1 — 1 — 15 71.45 13 69.19

G 2 23 227.27 23 244.70 1 — 1 — 22 227.27 22 244.70

1 10 37.65 8 40.35 1 — 1 — 8 37.65 7 40.35

H

2 13 53.77 10 55.70 1 — 1 — 12 53.77 10 55.70

I 2 25 385.14 24 405.27 1 — 1 — 25 385.14 24 405.27

J 2 9 36.19 7 38.86 1 — 1 — 7 36.19 6 38.86

K 2 8 32.68 6 32.99 1 — 1 — 6 32.68 4 32.99

L 2 4 23.53 14 70.30 1 — 1 — 3 23.54 14 70.30

1 7 32.59 5 31.32 1 — 1 — 5 32.59 3 31.32

M

2 22 183.20 22 174.39 1 — 1 — 20 183.20 19 174.39

O 2 12 45.52 9 50.30 1 — 1 — 10 45.52 8 50.30

1 15 63.40 12 62.27 1 — 1 — 14 63.41 12 62.27

P

2 18 114.37 17 115.02 1 — 1 — 17 114.37 16 115.021 20 153.63 20 165.60 25 59.45 26 81.88 21 213.08 23 247.48

Q

2 17 88.60 16 95.09 27 75.04 27 85.04 19 163.65 20 180.131 2 20.11 2 19.75 1 — 1 — 1 20.11 1 19.75

S

2 26 429.02 26 432.22 1 — 1 — 26 429.02 26 432.221 5 26.96 15 88.81 1 — 1 — 4 26.96 15 88.81

T

2 11 38.91 18 126.53 1 — 1 — 9 38.91 17 126.531 6 28.83 4 28.46 23 18.77 25 26.86 11 47.60 9 55.33

U

2 24 251.26 25 411.92 22 0.79 22 0.72 24 252.04 25 412.64

V 2 19 133.45 19 131.53 1 — 1 — 18 133.45 18 131.53

FNIR @ FPIR

= 10

−3

4 0.00304 0.0030

11 0.020710 0.020221 0.038622 0.041215 0.031124 0.068623 0.0684

4 0.00308 0.0143

14 0.0286

7 0.0072

26 NA25 NA12 0.021420 0.037016 0.0333

1 0.00271 0.0027

13 0.0281

9 0.0195

27 NA19 0.036617 0.033618 0.0358

3 0.0028

Table 42: Tabulation of mean identification time results for Class A — Left and Right Index — greater than or equal to 20-second searches. Letter refers to the participant’s letter code found onthe footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification definedin Section 5, with Total indicating the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations arereported in seconds, but were originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the right of this

table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 135

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 2 3.71 1 3.89 1 — 1 — 2 3.71 1 3.89

C

2 4 6.62 3 7.00 1 — 1 — 4 6.62 3 7.001 19 48.97 22 72.20 27 4.12 27 6.82 20 53.09 22 79.02

D

2 23 55.36 26 84.23 28 4.29 28 9.21 21 59.65 27 93.441 1 3.71 2 4.13 1 — 1 — 1 3.71 2 4.13

E

2 13 41.57 11 41.51 1 — 1 — 12 41.57 11 41.511 8 31.92 8 33.70 1 — 1 — 8 31.92 8 33.70

F

2 15 46.18 13 48.76 1 — 1 — 13 46.18 13 48.761 6 19.65 5 20.00 1 — 1 — 6 19.65 5 20.00

G

2 24 62.98 20 64.89 1 — 1 — 22 62.98 20 64.891 20 49.13 19 61.06 1 — 1 — 15 49.13 19 61.06

H

2 22 52.05 17 60.24 1 — 1 — 19 52.05 17 60.241 25 63.06 21 71.35 1 — 1 — 23 63.06 21 71.35

I

2 21 51.59 18 60.52 1 — 1 — 18 51.59 18 60.521 7 26.88 6 28.69 1 — 1 — 7 26.88 6 28.69

J

2 29 80.54 27 85.49 1 — 1 — 27 80.54 26 85.491 3 5.51 4 10.07 1 — 1 — 3 5.51 4 10.08

L

2 5 12.52 7 30.67 1 — 1 — 5 12.52 7 30.671 9 32.39 9 34.52 1 — 1 — 9 32.39 9 34.52

M

2 30 90.51 28 95.91 1 — 1 — 30 90.51 28 95.911 12 38.17 12 41.76 1 — 1 — 11 38.17 12 41.76

O

2 26 78.80 25 83.65 1 — 1 — 24 78.80 25 83.651 17 47.81 16 54.11 25 3.52 25 3.24 17 51.33 16 57.34

Q

2 16 47.51 15 53.38 26 3.54 26 3.35 16 51.05 15 56.741 27 78.95 24 79.27 1 — 1 — 25 78.95 24 79.27

S

2 28 79.01 23 79.17 1 — 1 — 26 79.01 23 79.171 10 33.07

— NA 30 48.79

— NA 28 81.85

— NA

U

2 14 42.62

— NA 29 47.88

— NA 29 90.50

— NA

1 11 36.28 10 36.96 1 — 1 — 10 36.28 10 36.96

V

2 18 48.01 14 50.63 1 — 1 — 14 48.01 14 50.63

FNIR @ FPIR

= 10

−3

22 0.065421 0.0647

6 0.01635 0.0142

13 0.0259

7 0.0187

29 0.168428 0.168118 0.037117 0.032523 0.099824 0.1008

4 0.01161 0.0094

15 0.028710 0.023616 0.028814 0.027630 0.173627 0.163412 0.025711 0.0254

2 0.00983 0.0099

25 0.108926 0.113320 0.050019 0.0461

9 0.01928 0.0190

Table 43: Tabulation of mean identification time results for Class B — Left Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used todifferentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combined

search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were originally recordedto microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could not be

performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from

Table 10 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
136 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 1 3.70 1 3.74 1 — 1 — 1 3.70 1 3.74

C

2 4 6.54 3 6.74 1 — 1 — 4 6.54 3 6.741 19 50.07 22 72.46 27 3.71 27 6.57 19 53.78 24 79.03

D

2 22 53.98 27 85.48 28 4.69 28 9.49 20 58.67 27 94.981 2 4.68 2 4.14 1 — 1 — 2 4.68 2 4.14

E

2 13 40.27 11 40.45 1 — 1 — 12 40.27 11 40.451 8 32.28 8 34.19 1 — 1 — 8 32.28 8 34.19

F

2 16 46.58 14 49.37 1 — 1 — 14 46.58 14 49.371 5 11.80 5 12.33 1 — 1 — 5 11.80 5 12.33

G

2 14 41.12 13 44.17 1 — 1 — 13 41.12 13 44.171 20 50.97 18 61.22 1 — 1 — 17 50.97 18 61.22

H

2 21 52.86 16 60.09 1 — 1 — 18 52.86 16 60.091 25 63.57 21 71.23 1 — 1 — 23 63.57 21 71.23

I

2 18 49.18 17 60.26 1 — 1 — 16 49.18 17 60.261 7 25.86 6 28.48 1 — 1 — 7 25.86 6 28.48

J

2 29 77.67 26 84.26 1 — 1 — 27 77.67 26 84.261 3 5.49 4 10.59 1 — 1 — 3 5.49 4 10.59

L

2 6 12.66 7 31.95 1 — 1 — 6 12.66 7 31.951 10 33.43 9 35.23 1 — 1 — 9 33.43 9 35.23

M

2 30 91.42 28 96.58 1 — 1 — 30 91.42 28 96.581 12 38.08 12 41.40 1 — 1 — 11 38.08 12 41.40

O

2 28 77.37 25 82.92 1 — 1 — 26 77.37 25 82.921 24 59.28 20 64.86 26 3.67 25 3.29 22 62.95 20 68.15

Q

2 23 57.74 19 62.96 25 3.56 26 3.35 21 61.29 19 66.311 27 74.29 23 76.78 1 — 1 — 25 74.29 22 76.78

S

2 26 73.96 24 77.18 1 — 1 — 24 73.96 23 77.181 9 33.35

— NA 30 56.35

— NA 29 89.71

— NA

U

2 15 42.87

— NA 29 46.01

— NA 28 88.88

— NA

1 11 35.66 10 37.19 1 — 1 — 10 35.66 10 37.19

V

2 17 48.47 15 50.37 1 — 1 — 15 48.47 15 50.37

FNIR @ FPIR

= 10

−3

24 0.040323 0.0392

6 0.00722 0.0052

13 0.0151

7 0.0083

29 0.122228 0.122018 0.021216 0.019825 0.064126 0.0647

5 0.00581 0.0045

14 0.015610 0.012615 0.016717 0.020230 0.125927 0.115512 0.014211 0.0132

3 0.00573 0.0057

21 0.036922 0.038119 0.026620 0.0273

8 0.01069 0.0110

Table 44: Tabulation of mean identification time results for Class B — Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to

differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combinedsearch time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were originally recordedto microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could not be

performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values fromTable 11 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 137

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 2 7.36 3 7.86 1 — 1 — 2 7.36 3 7.86

C

2 5 10.63 4 11.08 1 — 1 — 5 10.63 4 11.081 23 67.64 27 120.11 27 1.72 27 3.14 21 69.35 27 123.25

D

2 25 71.41 28 124.70 28 2.80 28 5.36 24 74.21 28 130.061 3 8.18 2 7.40 1 — 1 — 3 8.18 2 7.40

E

2 13 39.56 9 40.38 1 — 1 — 12 39.56 9 40.381 8 28.72 7 30.42 1 — 1 — 8 28.72 7 30.42

F

2 11 38.37 10 40.60 1 — 1 — 10 38.37 10 40.601 1 5.52 1 5.43 1 — 1 — 1 5.52 1 5.43

G

2 16 42.86 13 43.96 1 — 1 — 14 42.86 13 43.961 24 70.12 24 85.94 1 — 1 — 22 70.12 24 85.94

H

2 26 72.35 23 84.76 1 — 1 — 23 72.35 23 84.761 17 47.35 15 53.29 1 — 1 — 15 47.35 15 53.29

I

2 21 57.94 20 73.10 1 — 1 — 19 57.94 20 73.101 7 27.52 6 29.91 1 — 1 — 7 27.52 6 29.91

J

2 28 75.92 22 80.17 1 — 1 — 26 75.92 22 80.171 4 10.37 5 22.54 1 — 1 — 4 10.37 5 22.54

L

2 6 20.85 18 63.37 1 — 1 — 6 20.85 18 63.371 9 28.89 8 30.58 1 — 1 — 9 28.89 8 30.58

M

2 18 49.50 14 52.63 1 — 1 — 16 49.50 14 52.631 15 40.42 12 43.46 1 — 1 — 13 40.42 12 43.46

O

2 27 74.57 21 78.24 1 — 1 — 25 74.57 21 78.241 22 62.90 19 71.42 26 1.10 26 0.84 20 63.99 19 72.27

Q

2 19 52.85 17 61.10 25 1.03 25 0.78 18 53.88 17 61.881 30 85.05 26 87.49 1 — 1 — 28 85.05 26 87.49

S

2 29 84.02 25 87.27 1 — 1 — 27 84.02 25 87.271 10 30.21

— NA 30 56.68

— NA 29 86.88

— NA

U

2 14 40.05

— NA 29 50.99

— NA 30 91.04

— NA

1 12 39.24 11 41.22 1 — 1 — 11 39.24 11 41.22

V

2 20 52.97 16 55.45 1 — 1 — 17 52.97 16 55.45

FNIR @ FPIR

= 10

−3

30 NA29 NA

6 0.00315 0.0024

15 0.006310 0.004928 0.091026 0.090118 0.010617 0.008423 0.034924 0.0361

3 0.00221 0.0015

16 0.0068

9 0.0047

12 0.005414 0.006227 0.090425 0.088213 0.005711 0.0051

2 0.00213 0.0022

21 0.016022 0.019020 0.013919 0.0124

7 0.00367 0.0036

Table 45: Tabulation of mean identification time results for Class B — Left and Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier usedto differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combined

search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were originally recordedto microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could not be

performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from

Table 12 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
138 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 3 9.00 3 9.11 1 — 1 — 3 9.00 3 9.11

C

2 4 10.28 4 10.71 1 — 1 — 4 10.28 4 10.711 18 51.42 25 96.25 25 1.00 27 1.80 17 52.42 26 98.05

D

2 20 52.57 28 101.77 28 1.80 28 3.26 19 54.37 28 105.021 2 8.76 2 8.63 1 — 1 — 2 8.76 2 8.63

E

2 21 52.88 15 54.84 1 — 1 — 18 52.88 15 54.841 13 39.12 11 40.86 1 — 1 — 12 39.12 11 40.86

F

2 19 51.59 14 54.45 1 — 1 — 16 51.59 14 54.451 1 6.33 1 5.99 1 — 1 — 1 6.33 1 5.99

G

2 10 31.67 5 27.42 1 — 1 — 9 31.67 5 27.421 27 82.43 26 97.35 1 — 1 — 26 82.43 25 97.35

H

2 28 85.74 27 98.29 1 — 1 — 27 85.74 27 98.291 6 24.57 7 29.56 1 — 1 — 6 24.57 7 29.56

I

2 22 60.01 20 78.97 1 — 1 — 20 60.01 20 78.971 7 26.31 6 28.07 1 — 1 — 7 26.31 6 28.07

J

2 24 64.38 18 69.51 1 — 1 — 22 64.38 18 69.511 5 14.42 8 34.20 1 — 1 — 5 14.42 8 34.20

L

2 8 28.56 22 86.45 1 — 1 — 8 28.56 22 86.451 14 41.37 12 43.38 1 — 1 — 13 41.37 12 43.38

M

2 26 70.45 19 74.53 1 — 1 — 23 70.45 19 74.531 12 37.04 10 39.70 1 — 1 — 11 37.04 10 39.70

O

2 23 63.87 17 68.54 1 — 1 — 21 63.87 17 68.541 16 47.38 16 56.48 27 1.47 25 1.02 14 48.85 16 57.50

Q

2 25 70.21 21 81.92 26 1.46 26 1.05 24 71.67 21 82.971 29 86.50 23 91.50 1 — 1 — 28 86.50 23 91.50

S

2 30 88.70 24 93.61 1 — 1 — 29 88.70 24 93.611 9 30.33

— NA 30 58.50

— NA 30 88.83

— NA

U

2 15 42.51

— NA 29 37.63

— NA 25 80.14

— NA

1 11 35.50 9 37.75 1 — 1 — 10 35.51 9 37.75

V

2 17 49.72 13 51.37 1 — 1 — 15 49.72 13 51.37

FNIR @ FPIR

= 10

−3

30 NA29 NA

6 0.00202 0.0012

16 0.0043

7 0.0024

27 0.059127 0.059118 0.006214 0.004023 0.020324 0.0204

2 0.00121 0.0009

17 0.004911 0.003310 0.003111 0.003326 0.054325 0.051515 0.004113 0.0035

2 0.00122 0.0012

20 0.010821 0.013619 0.009922 0.0141

9 0.00277 0.0024

Table 46: Tabulation of mean identification time results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier usedto differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating the combined

search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were originally recordedto microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the value could not be

performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values fromTable 13 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 139

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 5 21.04 4 22.92 1 — 1 — 5 21.04 4 22.92

C

2 4 18.31 3 19.18 1 — 1 — 4 18.31 3 19.181 28 85.52 28 173.53 25 1.55 27 2.52 28 87.07 28 176.06

D

2 25 82.82 27 166.16 28 2.09 28 2.98 25 84.92 27 169.131 2 15.94 2 15.93 1 — 1 — 2 15.94 2 15.93

E

2 27 85.50 22 88.32 1 — 1 — 27 85.50 22 88.321 16 50.99 12 50.83 1 — 1 — 14 50.99 12 50.83

F

2 18 60.33 14 60.33 1 — 1 — 16 60.34 14 60.331 1 11.21 1 14.65 1 — 1 — 1 11.21 1 14.65

G

2 7 37.15 10 48.42 1 — 1 — 7 37.15 9 48.421 21 67.90 19 77.93 1 — 1 — 19 67.91 19 77.93

H

2 20 64.90 18 72.52 1 — 1 — 18 64.90 18 72.521 23 79.70 21 84.04 1 — 1 — 23 79.70 21 84.04

I

2 17 56.93 15 64.06 1 — 1 — 15 56.93 15 64.061 12 46.32 13 50.85 1 — 1 — 12 46.32 13 50.85

J

2 26 85.17 25 94.45 1 — 1 — 26 85.17 25 94.451 3 17.53 5 39.66 1 — 1 — 3 17.53 5 39.67

L

2 6 21.26 17 67.26 1 — 1 — 6 21.26 17 67.271 9 42.60 6 42.17 1 — 1 — 8 42.60 6 42.17

M

2 11 45.96 8 45.71 1 — 1 — 11 45.96 7 45.711 22 73.31 20 80.40 1 — 1 — 21 73.31 20 80.40

O

2 24 82.13 23 91.94 1 — 1 — 24 82.13 23 91.941 10 43.10 9 47.65 26 1.64 26 1.54 10 44.75 10 49.18

Q

2 8 41.98 7 45.57 27 1.70 25 1.39 9 43.67 8 46.961 29 87.76 26 97.78 1 — 1 — 29 87.76 26 97.78

S

2 30 89.24 24 92.85 1 — 1 — 30 89.24 24 92.851 13 47.49

— NA 30 27.65

— NA 22 75.14

— NA

U

2 15 50.30

— NA 29 17.68

— NA 20 67.98

— NA

1 14 47.76 11 49.30 1 — 1 — 13 47.76 11 49.30

V

2 19 63.19 16 66.29 1 — 1 — 17 63.19 16 66.29

FNIR @ FPIR

= 10

−3

30 NA24 0.0711

6 0.00152 0.0011

14 0.008813 0.004825 0.073425 0.073423 0.036820 0.027620 0.027619 0.0275

4 0.00131 0.0010

12 0.004710 0.002716 0.010215 0.009528 0.093427 0.0826

9 0.0025

10 0.0027

2 0.00114 0.0013

22 0.031129 0.168018 0.016317 0.0155

7 0.00247 0.0024

Table 47: Tabulation of mean identification time results for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were

originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,

the FNIR values from Table 14 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
140 FPVTE – FINGERPRINT MATCHING

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 4 25.25 3 27.50 1 — 1 — 4 25.25 3 27.50

C

2 5 25.91 4 27.89 1 — 1 — 5 25.91 4 27.891 18 61.79 27 102.45 28 4.17 25 1.91 17 65.97 27 104.36

D

2 28 83.58 28 160.54 27 2.81 28 3.02 30 86.39 28 163.561 1 9.52 1 10.54 1 — 1 — 1 9.52 1 10.54

E

2 16 57.01 13 59.56 1 — 1 — 14 57.02 13 59.561 15 55.63 11 58.39 1 — 1 — 13 55.63 11 58.39

F

2 20 68.61 18 71.58 1 — 1 — 18 68.61 18 71.581 2 11.67 2 12.99 1 — 1 — 2 11.67 2 12.99

G

2 6 30.61 5 31.33 1 — 1 — 6 30.61 5 31.331 29 84.14 25 94.22 1 — 1 — 28 84.14 25 94.22

H

2 30 84.26 26 94.72 1 — 1 — 29 84.26 26 94.721 25 79.04 19 75.61 1 — 1 — 24 79.04 19 75.61

I

2 9 40.53 7 41.07 1 — 1 — 9 40.53 7 41.071 8 36.09 6 40.14 1 — 1 — 8 36.09 6 40.14

J

2 22 72.62 23 81.37 1 — 1 — 20 72.62 22 81.371 7 31.42 14 64.18 1 — 1 — 7 31.42 14 64.19

L

2 3 19.51 12 58.45 1 — 1 — 3 19.52 12 58.451 11 47.38 9 49.47 1 — 1 — 11 47.38 9 49.47

M

2 13 48.71 10 50.67 1 — 1 — 12 48.71 10 50.671 17 59.01 15 66.17 1 — 1 — 15 59.01 15 66.17

O

2 21 72.55 22 81.31 1 — 1 — 19 72.55 21 81.311 26 81.02 24 82.87 25 2.23 26 2.53 26 83.25 24 85.39

Q

2 27 81.05 21 81.03 26 2.30 27 2.55 27 83.35 23 83.581 24 74.01 20 80.86 1 — 1 — 22 74.01 20 80.86

S

2 23 72.95 17 71.01 1 — 1 — 21 72.95 17 71.011 12 48.52

— NA 30 34.24

— NA 25 82.76

— NA

U

2 14 53.02

— NA 29 21.36

— NA 23 74.39

— NA

1 10 40.94 8 42.49 1 — 1 — 10 40.94 8 42.49

V

2 19 65.47 16 67.92 1 — 1 — 16 65.47 16 67.92

FNIR @ FPIR

= 10

−3

16 0.009415 0.0085

4 0.00157 0.0018

18 0.010612 0.005025 0.053625 0.053624 0.044721 0.033320 0.020119 0.0199

1 0.00132 0.0014

13 0.0051

9 0.0033

17 0.009714 0.008328 0.078327 0.071611 0.0034

9 0.00335 0.00172 0.0014

29 0.086030 0.246223 0.035822 0.0351

5 0.00178 0.0019

Table 48: Tabulation of mean identification time results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but wereoriginally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,the FNIR values from Table 15 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 141

Participant Stage One Stage Two Total

Letter Sub. # One Ten One Ten One Ten

1 7 36.55 4 40.68 1 — 1 — 7 36.55 4 40.68

C

2 5 33.93 3 35.83 1 — 1 — 5 33.93 3 35.831 14 55.60 27 98.54 25 0.77 25 0.71 12 56.38 27 99.25

D

2 25 74.38 28 155.17 26 1.62 27 1.90 25 76.00 28 157.061 1 10.81 1 11.40 1 — 1 — 1 10.81 1 11.40

E

2 18 59.20 15 61.17 1 — 1 — 16 59.20 15 61.171 17 58.39 14 58.89 1 — 1 — 15 58.39 14 58.89

F

2 19 61.82 16 61.34 1 — 1 — 17 61.82 16 61.341 3 25.05 2 32.02 1 — 1 — 3 25.05 2 32.02

G

2 6 34.47 5 45.09 1 — 1 — 6 34.47 5 45.091 20 65.03 21 78.10 1 — 1 — 18 65.03 21 78.10

H

2 21 65.69 17 73.62 1 — 1 — 19 65.69 17 73.621 27 76.98 22 82.78 1 — 1 — 26 76.98 22 82.78

I

2 23 66.90 20 76.96 1 — 1 — 21 66.90 20 76.961 8 42.13 6 46.98 1 — 1 — 8 42.13 6 46.98

J

2 28 79.37 24 89.84 1 — 1 — 27 79.37 24 89.841 4 27.43 13 58.35 1 — 1 — 4 27.43 13 58.36

L

2 2 18.62 7 50.64 1 — 1 — 2 18.62 7 50.651 15 57.06 11 56.59 1 — 1 — 13 57.06 11 56.59

M

2 16 57.90 12 58.12 1 — 1 — 14 57.90 12 58.121 22 65.71 18 74.07 1 — 1 — 20 65.71 18 74.07

O

2 26 75.98 23 86.80 1 — 1 — 24 75.98 23 86.801 9 47.17 10 52.18 28 1.91 26 1.72 10 49.07 10 53.90

Q

2 10 47.87 9 51.32 27 1.85 28 2.36 11 49.72 9 53.681 30 89.37 26 96.29 1 — 1 — 30 89.37 26 96.29

S

2 29 89.34 25 90.28 1 — 1 — 29 89.34 25 90.281 11 48.44

— NA 30 34.07

— NA 28 82.50

— NA

U

2 13 53.32

— NA 29 20.14

— NA 23 73.46

— NA

1 12 48.91 8 50.94 1 — 1 — 9 48.91 8 50.94

V

2 24 71.28 19 74.86 1 — 1 — 22 71.28 19 74.86

FNIR @ FPIR

= 10

−3

17 0.014918 0.0169

6 0.00283 0.0018

16 0.013712 0.005627 0.251427 0.251424 0.064923 0.052120 0.029119 0.0285

2 0.00141 0.0011

13 0.0071

7 0.0034

15 0.013614 0.012930 0.306727 0.251410 0.0041

8 0.00364 0.00205 0.0022

25 0.101726 0.236622 0.037821 0.029511 0.0052

9 0.0039

Table 49: Tabulation of mean identification time results for Class C — Ten-Finger Plain-to-Rolled. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an

identifier used to differentiate between the two submissions each participant could make. Stage One and Stage Two refer to the stages of identification defined in Section 5, with Total indicating

the combined search time. One and Ten refer to the number of concurrent identification processes run on a compute node. All values are mean durations are reported in seconds, but were

originally recorded to microsecond precision. A

— indicates that the operation completed faster than could be reliably measured. NA indicates that the operations required to produce the

value could not be performed. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference,

the FNIR values from Table 16 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
142 FPVTE – FINGERPRINT MATCHING

E Progression for Last Two Submissions

This appendix provides additional information in reference to comments from Section 8 that looked at accuracy versus

search time. The tables in this appendix show search times for the last two of the three submission periods during the

evaluation. Generally, participants attempt to improve accuracy with potential tradeoffs in speed and template size. The

tables in this section show the search times and FNIR @ FPIR = 10−3for the these two submissions.

Class A results are in Tables 50 through 52, Class B results are in Tables 53 through 56, and Class C results are in Tables 57

through 59.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 143

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

< 20 seconds

1 1 0.12 16 0.1077 1 0.29 24 0.1335

C

2 6 0.75 15 0.0984 6 0.87 25 0.1337

D 1 9 1.79 2 0.0376 20 7.52 1 0.0197

1 3 0.42 10 0.0794 4 0.57 12 0.0745

E

2 22 15.40 8 0.0757 30 16.71 11 0.0723

1 11 2.50 18 0.1122 11 2.52 20 0.1111

F

2 15 3.64 17 0.1093 15 3.78 18 0.1082

G 1 16 5.30 23 0.1221 21 9.52 19 0.1089

1 5 0.71 20 0.1168 14 3.65 26 0.1576

H

2 7 0.94 19 0.1160 17 4.26 27 0.1607

I 1 18 6.19 1 0.0306 22 10.36 5 0.0257

1 2 0.35 13 0.0900 3 0.56 14 0.0786

J

2 4 0.60 9 0.0773 7 1.34 10 0.0712

1 — — — — 25 10.48 17 0.0883

K

2 — — — — 24 10.47 16 0.0875

1 8 1.76 14 0.0913 2 0.30 8 0.0625

L

2 14 3.04 12 0.0881 12 3.34 6 0.0351

1 — — — — 10 2.07 29 0.2995

M

2 — — — — 27 15.19 28 0.2921

1 10 1.96 7 0.0751 5 0.64 15 0.0818

O

2 13 2.95 6 0.0735 9 1.63 13 0.0766

1 — — — — 8 1.38 23 0.1308

P

2 12 2.83 24 0.1343 13 3.43 22 0.1272

1 20 6.97 4 0.0507 29 15.90 2 0.0222

Q

2 19 6.42 5 0.0511 23 10.42 3 0.0226

S 1 17 5.99 11 0.0811 28 15.37 7 0.0571

1 23 16.49 21 0.1181 16 4.18 30 NA

T

2 — — — — 18 5.96 9 0.0685

U 1 24 18.62 22 0.1209 26 14.72 21 0.1218

V 1 21 10.34 3 0.0402 19 6.22 4 0.0253

≥ 20 seconds

D 2 1 3.99 1 0.0269 2 42.64 1 0.0197

G 2 4 27.35 5 0.1210 5 54.24 5 0.1086

I 2 3 9.04 2 0.0274 3 43.24 3 0.0278

S 2 2 5.94 4 0.0811 4 45.59 4 0.0650

U 2 — — — — 1 25.66 6 0.1178

V 2 5 61.50 3 0.0395 6 66.23 2 0.0252

Table 50: Tabulation of the progression of identification timing and accuracy for Class A — Left Index. Submissions were split into two groups. The first

group includes submissions that, in Third, performed searches on average in less than 20 seconds, and the second includes those that took, on average,

20 seconds or longer. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the

two submissions each participant could make. The Time column shows the time used to perform a search over an enrollment set of 100 000 in seconds,

but was originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA indicates that the

operations required to produce the value could not be performed. — indicates that there was not a validated submission during that submission period.

The number to the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
144 FPVTE – FINGERPRINT MATCHING

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

< 20 seconds

1 1 0.11 20 0.1022 1 0.25 24 0.1132

C

2 6 0.67 15 0.0899 6 0.76 23 0.1124

D 1 9 1.77 5 0.0337 20 7.68 1 0.0190

1 2 0.37 12 0.0733 3 0.45 11 0.0630

E

2 23 14.66 10 0.0709 30 15.89 10 0.0624

1 11 2.26 18 0.0945 11 2.52 20 0.0933

F

2 15 3.30 17 0.0928 15 3.71 18 0.0903

G 1 16 5.39 19 0.1018 21 10.12 19 0.0910

1 5 0.65 22 0.1035 14 3.58 26 0.1230

H

2 7 0.88 21 0.1025 17 4.13 27 0.1249

I 1 17 5.91 1 0.0232 23 10.19 3 0.0215

1 3 0.37 14 0.0800 4 0.53 16 0.0708

J

2 4 0.55 9 0.0700 7 1.25 12 0.0643

1 — — — — 25 10.42 14 0.0682

K

2 — — — — 24 10.30 15 0.0685

1 8 1.54 13 0.0739 2 0.29 8 0.0505

L

2 14 2.94 11 0.0721 12 3.26 6 0.0295

1 — — — — 10 1.75 30 0.2615

M

2 — — — — 26 11.31 29 0.2526

1 10 1.89 7 0.0672 5 0.59 17 0.0776

O

2 13 2.79 8 0.0673 9 1.48 13 0.0675

1 — — — — 8 1.38 25 0.1133

P

2 12 2.62 24 0.1120 13 3.49 22 0.1100

1 22 12.96 3 0.0248 28 14.44 4 0.0218

Q

2 19 9.23 2 0.0242 22 10.15 2 0.0214

S 1 18 6.18 6 0.0640 29 15.08 7 0.0442

1 21 12.30 16 0.0924 16 3.82 28 0.1929

T

2 — — — — 18 5.64 9 0.0562

U 1 24 15.97 23 0.1048 27 12.02 21 0.0996

V 1 20 9.96 4 0.0331 19 5.95 5 0.0223

≥ 20 seconds

D 2 2 6.25 2 0.0248 2 29.26 1 0.0190

G 2 4 26.76 5 0.1007 5 57.88 5 0.0909

I 2 3 9.31 1 0.0217 3 41.60 2 0.0214

S 2 1 6.20 4 0.0641 4 43.56 4 0.0503

U 2 — — — — 1 22.39 6 0.1007

V 2 5 60.50 3 0.0330 6 64.47 3 0.0222

Table 51: Tabulation of the progression of identification timing and accuracy for Class A — Right Index. Submissions were split into two groups. The first

group includes submissions that, in Third, performed searches on average in less than 20 seconds, and the second includes those that took, on average,

20 seconds or longer. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the

two submissions each participant could make. The Time column shows the time used to perform a search over an enrollment set of 100 000 in seconds,

but was originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. — indicates that there was

not a validated submission during that submission period. The number to the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 145

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

< 20 seconds

1 1 1.48 6 0.0313 2 2.39 7 0.0368

C

2 2 6.30 7 0.0354 4 6.34 8 0.0374

G 1 3 7.38 8 0.1426 3 6.27 9 0.0515

I 1 7 19.73 2 0.0073 9 18.92 2 0.0058

J 1 5 9.20 4 0.0161 6 14.00 3 0.0143

K 1 — — — — 8 18.32 6 0.0360

L 1 6 17.81 5 0.0306 1 2.20 4 0.0146

O 1 8 57.36 3 0.0132 7 15.34 5 0.0229

V 1 4 8.56 1 0.0056 5 9.50 1 0.0034

≥ 20 seconds

1 2 14.06 5 0.0046 16 73.01 4 0.0030

D

2 9 46.57 1 0.0033 23 234.52 4 0.0030

1 4 17.36 10 0.0216 2 22.27 11 0.0207

E

2 22 463.95 9 0.0208 27 500.30 10 0.0202

1 12 56.49 15 0.0392 13 59.30 21 0.0386

F

2 13 67.36 16 0.0407 15 71.45 22 0.0412

G 2 19 166.37 21 0.0558 22 227.27 15 0.0311

1 5 18.42 20 0.0538 8 37.65 24 0.0686

H

2 6 25.38 19 0.0537 12 53.77 23 0.0684

I 2 18 162.34 4 0.0038 25 385.14 4 0.0030

J 2 3 16.23 8 0.0137 7 36.19 8 0.0143

K 2 — — — — 6 32.68 14 0.0286

L 2 7 34.31 13 0.0365 3 23.54 7 0.0072

1 — — — — 5 32.59 26 NA

M

2 — — — — 20 183.20 25 NA

O 2 15 85.37 7 0.0134 10 45.52 12 0.0214

1 — — — — 14 63.41 20 0.0370

P

2 16 89.78 17 0.0408 17 114.37 16 0.0333

1 14 85.29 3 0.0035 21 213.08 1 0.0027

Q

2 10 48.40 2 0.0034 19 163.65 1 0.0027

1 1 13.37 14 0.0379 1 20.11 13 0.0281

S

2 11 54.11 11 0.0316 26 429.02 9 0.0195

1 17 138.43 12 0.0318 4 26.96 27 NA

T

2 — — — — 9 38.91 19 0.0366

1 8 38.87 18 0.0532 11 47.60 17 0.0336

U

2 21 288.82 22 0.2620 24 252.04 18 0.0358

V 2 20 197.77 6 0.0048 18 133.45 3 0.0028

Table 52: Tabulation of the progression of identification timing and accuracy for Class A — Left and Right Index. Submissions were split into two groups.

The first group includes submissions that, in Third, performed searches on average in less than 20 seconds, and the second includes those that took, on

average, 20 seconds or longer. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate

between the two submissions each participant could make. The Time column shows the time used to perform a search over an enrollment set of 1 600 000

in seconds, but was originally recorded to microsecond precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA indicates

that the operations required to produce the value could not be performed. — indicates that there was not a validated submission during that submission

period. The number to the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
146 FPVTE – FINGERPRINT MATCHING

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 1 3.20 14 0.0667 2 3.71 22 0.0654

C

2 3 6.18 15 0.0669 4 6.62 21 0.0647

1 14 39.90 5 0.0178 20 53.09 6 0.0163

D

2 18 55.83 7 0.0242 21 59.65 5 0.0142

1 2 3.37 12 0.0397 1 3.71 13 0.0259

E

2 7 19.68 8 0.0277 12 41.57 7 0.0187

1 — — — — 8 31.92 29 0.1684

F

2 — — — — 13 46.18 28 0.1681

1 12 33.42 17 0.0704 6 19.65 18 0.0371

G

2 19 61.44 16 0.0677 22 62.98 17 0.0325

1 13 39.16 18 0.0798 15 49.13 23 0.0998

H

2 17 46.21 20 0.0813 19 52.05 24 0.1008

1 21 77.87 4 0.0161 23 63.06 4 0.0116

I

2 20 67.21 3 0.0127 18 51.59 1 0.0094

1 5 11.15 13 0.0491 7 26.88 15 0.0287

J

2 11 31.32 9 0.0340 27 80.54 10 0.0236

1 4 10.66 19 0.0809 3 5.51 16 0.0288

L

2 8 23.68 20 0.0813 5 12.52 14 0.0276

1 — — — — 9 32.39 30 0.1736

M

2 22 89.64 22 0.1634 30 90.51 27 0.1634

1 6 19.29 11 0.0366 11 38.17 12 0.0257

O

2 9 30.71 10 0.0349 24 78.80 11 0.0254

1 16 45.67 1 0.0104 17 51.33 2 0.0098

Q

2 10 31.26 2 0.0116 16 51.05 3 0.0099

1 — — — — 25 78.95 25 0.1089

S

2 — — — — 26 79.01 26 0.1133

1 — — — — 28 81.85 20 0.0500

U

2 — — — — 29 90.50 19 0.0461

1 15 42.01 6 0.0239 10 36.28 9 0.0192

V

2 — — — — 14 48.01 8 0.0190

Table 53: Tabulation of the progression of identification timing and accuracy for Class B — Left Slap. Letter refers to the participant’s letter code found

on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The Time column shows

the time used to perform a search over an enrollment set of 3 000 000 in seconds, but was originally recorded to microsecond precision. The FNIR column

shows FNIR for each submission at FPIR = 10−3. — indicates that there was not a validated submission during that submission period. The number to

the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 147

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 1 3.16 16 0.0391 1 3.70 24 0.0403

C

2 3 6.10 14 0.0386 4 6.54 23 0.0392

1 13 37.74 5 0.0082 19 53.78 6 0.0072

D

2 19 56.55 6 0.0100 20 58.67 2 0.0052

1 2 3.71 11 0.0220 2 4.68 13 0.0151

E

2 9 25.48 7 0.0134 12 40.27 7 0.0083

1 — — — — 8 32.28 29 0.1222

F

2 — — — — 14 46.58 28 0.1220

1 6 19.93 17 0.0423 5 11.80 18 0.0212

G

2 15 41.42 15 0.0388 13 41.12 16 0.0198

1 14 39.40 20 0.0554 17 50.97 25 0.0641

H

2 17 46.02 21 0.0563 18 52.86 26 0.0647

1 21 79.29 4 0.0074 23 63.57 5 0.0058

I

2 20 77.42 1 0.0057 16 49.18 1 0.0045

1 5 11.62 13 0.0313 7 25.86 14 0.0156

J

2 11 32.12 9 0.0210 27 77.67 10 0.0126

1 4 11.09 18 0.0526 3 5.49 15 0.0167

L

2 8 23.42 19 0.0536 6 12.66 17 0.0202

1 — — — — 9 33.43 30 0.1259

M

2 22 90.28 22 0.1157 30 91.42 27 0.1155

1 7 20.12 12 0.0231 11 38.08 12 0.0142

O

2 10 32.04 10 0.0212 26 77.37 11 0.0132

1 18 53.98 2 0.0064 22 62.95 3 0.0057

Q

2 12 33.57 3 0.0069 21 61.29 3 0.0057

1 — — — — 25 74.29 21 0.0369

S

2 — — — — 24 73.96 22 0.0381

1 — — — — 29 89.71 19 0.0266

U

2 — — — — 28 88.88 20 0.0273

1 16 42.11 8 0.0148 10 35.66 8 0.0106

V

2 — — — — 15 48.47 9 0.0110

Table 54: Tabulation of the progression of identification timing and accuracy for Class B — Right Slap. Letter refers to the participant’s letter code found

on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The Time column shows

the time used to perform a search over an enrollment set of 3 000 000 in seconds, but was originally recorded to microsecond precision. The FNIR column

shows FNIR for each submission at FPIR = 10−3. — indicates that there was not a validated submission during that submission period. The number to

the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
148 FPVTE – FINGERPRINT MATCHING

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 1 3.44 21 0.0365 2 7.36 30 NA

C

2 3 4.33 20 0.0356 5 10.63 29 NA

1 13 38.51 5 0.0040 21 69.35 6 0.0031

D

2 17 48.86 6 0.0045 24 74.21 5 0.0024

1 4 6.39 11 0.0098 3 8.18 15 0.0063

E

2 18 52.30 8 0.0074 12 39.56 10 0.0049

1 — — — — 8 28.72 28 0.0910

F

2 — — — — 10 38.37 26 0.0901

1 2 4.27 13 0.0132 1 5.52 18 0.0106

G

2 7 22.15 16 0.0235 14 42.86 17 0.0084

1 19 52.34 18 0.0325 22 70.12 23 0.0349

H

2 20 61.14 19 0.0340 23 72.35 24 0.0361

1 22 79.56 4 0.0031 15 47.35 3 0.0022

I

2 21 69.84 3 0.0027 19 57.94 1 0.0015

1 5 11.06 15 0.0228 7 27.52 16 0.0068

J

2 12 32.23 10 0.0090 26 75.92 9 0.0047

1 8 25.03 17 0.0312 4 10.37 12 0.0054

L

2 10 26.13 14 0.0216 6 20.85 14 0.0062

1 — — — — 9 28.89 27 0.0904

M

2 16 48.74 22 0.0882 16 49.50 25 0.0882

1 6 19.15 12 0.0106 13 40.42 13 0.0057

O

2 11 31.55 9 0.0088 25 74.57 11 0.0051

1 15 47.54 1 0.0019 20 63.99 2 0.0021

Q

2 9 25.99 2 0.0020 18 53.88 3 0.0022

1 — — — — 28 85.05 21 0.0160

S

2 — — — — 27 84.02 22 0.0190

1 — — — — 29 86.88 20 0.0139

U

2 — — — — 30 91.04 19 0.0124

1 14 46.90 7 0.0051 11 39.24 7 0.0036

V

2 — — — — 17 52.97 7 0.0036

Table 55: Tabulation of the progression of identification timing and accuracy for Class B — Left and Right Slap. Letter refers to the participant’s letter code

found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The Time column

shows the time used to perform a search over an enrollment set of 3 000 000 in seconds, but was originally recorded to microsecond precision. The FNIR

column shows FNIR for each submission at FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. —

indicates that there was not a validated submission during that submission period. The number to the left of a value provides the value’s column-wise

ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 149

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 2 4.67 20 0.0276 3 9.00 30 NA

C

2 3 5.01 19 0.0268 4 10.28 29 NA

1 9 26.83 6 0.0028 17 52.42 6 0.0020

D

2 13 33.98 5 0.0027 19 54.37 2 0.0012

1 4 7.71 11 0.0071 2 8.76 16 0.0043

E

2 20 70.09 8 0.0043 18 52.88 7 0.0024

1 — — — — 12 39.12 27 0.0591

F

2 — — — — 16 51.59 27 0.0591

1 1 2.50 12 0.0101 1 6.33 18 0.0062

G

2 6 12.62 14 0.0157 9 31.67 14 0.0040

1 18 56.70 16 0.0220 26 82.43 23 0.0203

H

2 19 67.68 17 0.0249 27 85.74 24 0.0204

1 22 75.61 4 0.0021 6 24.57 2 0.0012

I

2 17 50.74 2 0.0012 20 60.01 1 0.0009

1 5 8.13 22 0.0614 7 26.31 17 0.0049

J

2 11 31.60 9 0.0054 22 64.38 11 0.0033

1 14 36.59 18 0.0250 5 14.42 10 0.0031

L

2 12 33.50 13 0.0147 8 28.56 11 0.0033

1 — — — — 13 41.37 26 0.0543

M

2 21 70.37 21 0.0515 23 70.45 25 0.0515

1 7 16.34 15 0.0173 11 37.04 15 0.0041

O

2 10 30.74 10 0.0056 21 63.87 13 0.0035

1 16 48.59 1 0.0010 14 48.85 2 0.0012

Q

2 8 26.38 2 0.0012 24 71.67 2 0.0012

1 — — — — 28 86.50 20 0.0108

S

2 — — — — 29 88.70 21 0.0136

1 — — — — 30 88.83 19 0.0099

U

2 — — — — 25 80.14 22 0.0141

1 15 42.75 7 0.0041 10 35.51 9 0.0027

V

2 — — — — 15 49.72 7 0.0024

Table 56: Tabulation of the progression of identification timing and accuracy for Class B — Identification Flats. Letter refers to the participant’s letter code

found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The Time column

shows the time used to perform a search over an enrollment set of 3 000 000 in seconds, but was originally recorded to microsecond precision. The FNIR

column shows FNIR for each submission at FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. —

indicates that there was not a validated submission during that submission period. The number to the left of a value provides the value’s column-wise

ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
150 FPVTE – FINGERPRINT MATCHING

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 3 10.27 16 0.0574 5 21.04 30 NA

C

2 2 10.04 17 0.0584 4 18.31 24 0.0711

1 10 44.21 4 0.0024 28 87.07 6 0.0015

D

2 20 74.46 3 0.0018 25 84.92 2 0.0011

1 6 27.61 11 0.0143 2 15.94 14 0.0088

E

2 21 79.95 9 0.0083 27 85.50 13 0.0048

1 12 50.99 18 0.0734 14 50.99 25 0.0734

F

2 17 60.34 18 0.0734 16 60.34 25 0.0734

1 1 8.43 21 0.1923 1 11.21 23 0.0368

G

2 5 21.36 20 0.0780 7 37.15 20 0.0276

1 18 68.30 15 0.0377 19 67.91 20 0.0276

H

2 15 59.28 14 0.0363 18 64.90 19 0.0275

1 14 56.55 5 0.0033 23 79.70 4 0.0013

I

2 9 40.52 7 0.0050 15 56.93 1 0.0010

1 7 35.33 10 0.0104 12 46.32 12 0.0047

J

2 19 69.82 7 0.0050 26 85.17 10 0.0027

1 13 54.67 12 0.0159 3 17.53 16 0.0102

L

2 11 47.51 13 0.0221 6 21.26 15 0.0095

1 — — — — 8 42.60 28 0.0934

M

2 — — — — 11 45.96 27 0.0826

1 — — — — 21 73.31 9 0.0025

O

2 — — — — 24 82.13 10 0.0027

1 8 38.03 1 0.0014 10 44.75 2 0.0011

Q

2 4 20.02 2 0.0017 9 43.67 4 0.0013

1 — — — — 29 87.76 22 0.0311

S

2 — — — — 30 89.24 29 0.1680

1 — — — — 22 75.14 18 0.0163

U

2 — — — — 20 67.98 17 0.0155

1 16 59.38 6 0.0034 13 47.76 7 0.0024

V

2 — — — — 17 63.19 7 0.0024

Table 57: Tabulation of the progression of identification timing and accuracy for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s

letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make.

The Time column shows the time used to perform a search over an enrollment set of 5 000 000 in seconds, but was originally recorded to microsecond

precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA indicates that the operations required to produce the value could

not be performed. — indicates that there was not a validated submission during that submission period. The number to the left of a value provides the

value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 151

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 2 19.26 21 0.0826 4 25.25 16 0.0094

C

2 7 28.17 20 0.0822 5 25.91 15 0.0085

1 11 46.42 6 0.0028 17 65.97 4 0.0015

D

2 16 70.86 5 0.0023 30 86.39 7 0.0018

1 1 12.49 17 0.0285 1 9.52 18 0.0106

E

2 8 29.59 9 0.0121 14 57.02 12 0.0050

1 13 55.63 18 0.0536 13 55.63 25 0.0536

F

2 15 68.61 18 0.0536 18 68.61 25 0.0536

1 3 20.17 15 0.0239 2 11.67 24 0.0447

G

2 5 23.05 13 0.0195 6 30.61 21 0.0333

1 19 77.49 15 0.0239 28 84.14 20 0.0201

H

2 17 71.01 14 0.0237 29 84.26 19 0.0199

1 10 40.06 1 0.0015 24 79.04 1 0.0013

I

2 4 20.92 7 0.0032 9 40.53 2 0.0014

1 6 26.55 12 0.0168 8 36.09 13 0.0051

J

2 12 55.60 8 0.0045 20 72.62 9 0.0033

1 18 75.36 10 0.0123 7 31.42 17 0.0097

L

2 20 80.46 11 0.0160 3 19.52 14 0.0083

1 — — — — 11 47.38 28 0.0783

M

2 — — — — 12 48.71 27 0.0716

1 — — — — 15 59.01 11 0.0034

O

2 — — — — 19 72.55 9 0.0033

1 14 67.74 1 0.0015 26 83.25 5 0.0017

Q

2 9 37.87 3 0.0019 27 83.35 2 0.0014

1 — — — — 22 74.01 29 0.0860

S

2 — — — — 21 72.95 30 0.2462

1 — — — — 25 82.76 23 0.0358

U

2 — — — — 23 74.39 22 0.0351

1 21 91.48 4 0.0022 10 40.94 5 0.0017

V

2 — — — — 16 65.47 8 0.0019

Table 58: Tabulation of the progression of identification timing and accuracy for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s

letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make.

The Time column shows the time used to perform a search over an enrollment set of 5 000 000 in seconds, but was originally recorded to microsecond

precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. — indicates that there was not a validated submission during that

submission period. The number to the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
152 FPVTE – FINGERPRINT MATCHING

Participant Second Third

Letter Sub. # Time FNIR Time FNIR

1 3 18.23 16 0.0979 7 36.55 17 0.0149

C

2 4 19.43 17 0.1124 5 33.93 18 0.0169

1 8 39.02 6 0.0048 12 56.38 6 0.0028

D

2 14 58.60 2 0.0034 25 76.00 3 0.0018

1 5 20.29 13 0.0383 1 10.81 16 0.0137

E

2 10 55.20 9 0.0164 16 59.20 12 0.0056

1 13 58.39 20 0.2514 15 58.39 27 0.2514

F

2 16 61.82 20 0.2514 17 61.82 27 0.2514

1 1 11.46 19 0.2393 3 25.05 24 0.0649

G

2 2 11.62 18 0.1455 6 34.47 23 0.0521

1 20 70.66 15 0.0429 18 65.03 20 0.0291

H

2 18 62.51 14 0.0411 19 65.69 19 0.0285

1 11 56.80 5 0.0039 26 76.98 2 0.0014

I

2 12 58.34 4 0.0037 21 66.90 1 0.0011

1 7 30.56 10 0.0174 8 42.13 13 0.0071

J

2 17 62.05 8 0.0053 27 79.37 7 0.0034

1 15 60.76 11 0.0251 4 27.43 15 0.0136

L

2 21 72.40 12 0.0358 2 18.62 14 0.0129

1 — — — — 13 57.06 30 0.3067

M

2 — — — — 14 57.90 27 0.2514

1 — — — — 20 65.71 10 0.0041

O

2 — — — — 24 75.98 8 0.0036

1 9 42.45 1 0.0028 10 49.07 4 0.0020

Q

2 6 22.94 2 0.0034 11 49.72 5 0.0022

1 — — — — 30 89.37 25 0.1017

S

2 — — — — 29 89.34 26 0.2366

1 — — — — 28 82.50 22 0.0378

U

2 — — — — 23 73.46 21 0.0295

1 19 66.49 7 0.0051 9 48.91 11 0.0052

V

2 — — — — 22 71.28 9 0.0039

Table 59: Tabulation of the progression of identification timing and accuracy for Class C — Ten-Finger Plain-to-Rolled. Letter refers to the participant’s

letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make.

The Time column shows the time used to perform a search over an enrollment set of 5 000 000 in seconds, but was originally recorded to microsecond

precision. The FNIR column shows FNIR for each submission at FPIR = 10−3. — indicates that there was not a validated submission during that

submission period. The number to the left of a value provides the value’s column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 153

F Enrollment Size

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
154 FPVTE – FINGERPRINT MATCHING

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 7 0.18 10 0.16 8 0.17 8 0.16

C

2 8 0.18 10 0.16 8 0.17 8 0.16

1 21 0.61 18 0.33 29 1.25 18 0.34

D

2 21 0.61 18 0.33 30 1.40 18 0.34

1 30 1.12 27 0.50 23 0.50 27 0.50

E

2 29 1.11 27 0.50 23 0.50 27 0.50

1 6 0.18 7 0.11 10 0.17 10 0.17

F

2 5 0.18 7 0.11 10 0.17 10 0.17

1 20 0.57 29 0.50 5 0.15 5 0.15

G

2 19 0.57 29 0.50 5 0.15 5 0.15

1 11 0.33 14 0.29 12 0.29 14 0.29

H

2 11 0.33 14 0.29 12 0.29 14 0.29

1 23 0.70 35 0.68 31 1.54 35 0.68

I

2 28 1.04 36 1.03 32 1.55 36 1.03

1 9 0.32 12 0.27 14 0.31 12 0.28

J

2 9 0.32 12 0.27 14 0.31 12 0.28

1 35 3.87 25 0.47 35 4.60 25 0.48

K

2 36 3.87 25 0.47 35 4.60 25 0.48

1 31 1.14 9 0.15 7 0.16 7 0.16

L

2 34 2.32 22 0.46 20 0.46 22 0.46

1 3 0.14 5 0.11 3 0.13 3 0.13

M

2 4 0.14 5 0.11 3 0.13 3 0.13

1 15 0.35 16 0.30 16 0.32 16 0.31

O

2 15 0.35 16 0.30 16 0.32 16 0.31

1 27 0.78 3 0.03 1 0.03 1 0.03

P

2 26 0.78 3 0.03 1 0.03 1 0.03

1 13 0.34 1 0.03 27 1.07 33 0.68

Q

2 14 0.34 1 0.03 27 1.07 33 0.68

1 24 0.72 23 0.47 21 0.47 23 0.47

S

2 24 0.72 23 0.47 21 0.47 23 0.47

1 2 0.01 33 0.60 25 0.91 31 0.60

T

2 1 0.01 33 0.60 25 0.91 31 0.60

1 33 1.70 31 0.53 33 1.96 29 0.54

U

2 32 1.42 31 0.53 33 1.96 29 0.54

1 18 0.39 20 0.38 18 0.39 20 0.38

V

2 17 0.39 20 0.38 18 0.39 20 0.38

FNIR @ FPIR = 10−3

30 0.1335

31 0.1337

1 0.0197

1 0.0197

16 0.0745

15 0.0723

25 0.1111

22 0.1082

24 0.1089

23 0.1086

32 0.1576

33 0.1607

7 0.0257

8 0.0278

18 0.0786

14 0.0712

21 0.0883

20 0.0875

11 0.0625

9 0.0351

35 0.2995

34 0.2921

19 0.0818

17 0.0766

29 0.1308

28 0.1272

3 0.0222

4 0.0226

10 0.0571

12 0.0650

36 NA

13 0.0685

27 0.1218

26 0.1178

6 0.0253

5 0.0252

Table 60: Tabulation of storage and RAM requirements for Class A — Left Index, with an enrollment set size of 100 000 subjects. Submissions were split into two groups. The

first group includes submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter

refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make

during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM refers to the sum of the resident set sizes of

the stage one identification processes over all compute nodes after returning from the identification stage one initialization method. Reported RAM is the sum of the predicted

RAM consumption returned from the enrollment method when enrolling images for the enrollment set. Finalized Size is the amount of disk storage space used in the finalized

enrollment set directory after the finalization method returned. Stored Size is the actual amount of storage space used to hold the individual enrollment templates on disk,

determined by summing the number of bytes written by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 155

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 7 0.17 10 0.15 8 0.16 8 0.16

C

2 8 0.18 10 0.15 8 0.16 8 0.16

1 21 0.61 18 0.33 29 1.25 18 0.33

D

2 21 0.61 18 0.33 30 1.40 18 0.33

1 29 1.07 27 0.48 23 0.48 27 0.48

E

2 30 1.07 27 0.48 23 0.48 27 0.48

1 6 0.17 7 0.11 10 0.17 10 0.16

F

2 5 0.17 7 0.11 10 0.17 10 0.16

1 19 0.57 29 0.48 5 0.15 5 0.15

G

2 20 0.57 29 0.48 5 0.15 5 0.15

1 14 0.33 14 0.29 14 0.29 14 0.29

H

2 13 0.33 14 0.29 14 0.29 14 0.29

1 23 0.69 35 0.67 31 1.54 35 0.67

I

2 28 1.01 36 0.99 32 1.55 36 0.99

1 10 0.31 12 0.26 12 0.29 12 0.27

J

2 9 0.31 12 0.26 12 0.29 12 0.27

1 36 3.87 25 0.46 35 4.60 25 0.47

K

2 35 3.87 25 0.46 35 4.60 25 0.47

1 31 1.14 9 0.15 7 0.16 7 0.15

L

2 34 2.32 22 0.44 20 0.45 22 0.45

1 3 0.14 5 0.11 3 0.13 3 0.12

M

2 3 0.14 5 0.11 3 0.13 3 0.12

1 15 0.34 16 0.29 16 0.30 16 0.30

O

2 16 0.34 16 0.29 16 0.30 16 0.30

1 26 0.76 3 0.03 1 0.03 1 0.03

P

2 27 0.76 3 0.03 1 0.03 1 0.03

1 11 0.33 1 0.03 27 1.03 33 0.66

Q

2 11 0.33 1 0.03 27 1.03 33 0.66

1 24 0.71 23 0.46 21 0.46 23 0.46

S

2 25 0.71 23 0.46 21 0.46 23 0.46

1 1 0.01 33 0.57 25 0.87 31 0.57

T

2 1 0.01 33 0.57 25 0.87 31 0.57

1 33 1.56 31 0.52 33 1.79 29 0.52

U

2 32 1.30 31 0.52 33 1.79 29 0.52

1 18 0.39 20 0.38 18 0.38 20 0.38

V

2 17 0.39 20 0.38 18 0.38 20 0.38

FNIR @ FPIR = 10−3

30 0.1132

29 0.1124

1 0.0190

1 0.0190

15 0.0630

14 0.0624

25 0.0933

22 0.0903

24 0.0910

23 0.0909

32 0.1230

33 0.1249

5 0.0215

3 0.0214

20 0.0708

16 0.0643

18 0.0682

19 0.0685

12 0.0505

9 0.0295

36 0.2615

35 0.2526

21 0.0776

17 0.0675

31 0.1133

28 0.1100

6 0.0218

3 0.0214

10 0.0442

11 0.0503

34 0.1929

13 0.0562

26 0.0996

27 0.1007

8 0.0223

7 0.0222

Table 61: Tabulation of storage and RAM requirements for Class A — Right Index, with an enrollment set size of 100 000 subjects. Submissions were split into two groups.

The first group includes submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer.

Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM refers to the sum of the resident set

sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method. Reported RAM is the sum of the

predicted RAM consumption returned from the enrollment method when enrolling images for the enrollment set. Finalized Size is the amount of disk storage space used in the

finalized enrollment set directory after the finalization method returned. Stored Size is the actual amount of storage space used to hold the individual enrollment templates on

disk, determined by summing the number of bytes written by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
156 FPVTE – FINGERPRINT MATCHING

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 8 4.87 10 4.66 8 4.78 8 4.69

C

2 7 4.87 10 4.66 8 4.78 8 4.69

1 24 18.58 18 10.30 30 40.04 18 10.31

D

2 24 18.58 18 10.30 31 44.68 18 10.31

1 30 33.40 27 14.95 23 15.02 27 14.96

E

2 31 33.41 27 14.95 23 15.02 27 14.96

1 5 4.86 5 3.21 10 4.86 10 4.78

F

2 5 4.86 5 3.21 10 4.86 10 4.78

1 23 16.38 31 15.63 6 4.75 6 4.67

G

2 22 16.38 31 15.63 6 4.75 6 4.67

1 16 9.36 16 9.19 16 9.32 16 9.19

H

2 15 9.36 16 9.19 16 9.32 16 9.19

1 21 15.83 33 15.68 25 24.61 31 15.68

I

2 29 30.83 36 30.68 32 46.83 36 30.68

1 9 8.30 12 8.07 12 8.68 12 8.15

J

2 10 8.30 12 8.07 12 8.68 12 8.15

1 36 61.81 25 14.74 35 73.67 25 14.80

K

2 35 61.81 25 14.74 35 73.67 25 14.80

1 26 18.76 9 4.55 5 4.68 5 4.61

L

2 34 53.98 22 13.64 20 13.73 22 13.66

1 3 3.75 5 3.21 3 3.75 3 3.68

M

2 4 3.76 5 3.21 3 3.75 3 3.68

1 12 9.05 14 8.82 14 8.84 14 8.90

O

2 11 9.05 14 8.82 14 8.84 14 8.90

1 28 21.42 3 0.86 1 0.89 1 0.83

P

2 27 21.41 3 0.86 1 0.89 1 0.83

1 14 9.14 1 0.82 28 30.63 34 20.48

Q

2 13 9.14 1 0.82 28 30.63 34 20.48

1 19 14.82 23 14.57 21 14.63 23 14.57

S

2 19 14.82 23 14.57 21 14.63 23 14.57

1 1 0.01 34 17.99 26 27.40 32 18.02

T

2 1 0.01 34 17.99 26 27.40 32 18.02

1 33 44.63 29 15.30 33 51.84 29 15.46

U

2 32 37.35 29 15.30 33 51.84 29 15.46

1 18 11.77 20 11.69 18 11.77 20 11.71

V

2 17 11.77 20 11.69 18 11.77 20 11.71

FNIR @ FPIR = 10−3

26 0.0368

28 0.0374

4 0.0030

4 0.0030

15 0.0207

14 0.0202

29 0.0386

30 0.0412

31 0.0515

20 0.0311

33 0.0686

32 0.0684

8 0.0058

4 0.0030

10 0.0143

10 0.0143

24 0.0360

19 0.0286

12 0.0146

9 0.0072

35 NA

34 NA

17 0.0229

16 0.0214

27 0.0370

21 0.0333

1 0.0027

1 0.0027

18 0.0281

13 0.0195

36 NA

25 0.0366

22 0.0336

23 0.0358

7 0.0034

3 0.0028

Table 62: Tabulation of storage and RAM requirements for Class A — Left and Right Index, with an enrollment set size of 1 600 000 subjects. Submissions were split into two

groups. The first group includes submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or

longer. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant

could make during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM refers to the sum of the resident

set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method. Reported RAM is the sum of the

predicted RAM consumption returned from the enrollment method when enrolling images for the enrollment set. Finalized Size is the amount of disk storage space used in the

finalized enrollment set directory after the finalization method returned. Stored Size is the actual amount of storage space used to hold the individual enrollment templates on

disk, determined by summing the number of bytes written by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 157

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 3 46.49 4 45.92 2 46.34 2 45.98

C

2 4 46.49 4 45.92 2 46.34 2 45.98

1 12 79.43 16 84.51 18 86.78 18 86.59

D

2 13 79.43 15 83.67 15 85.95 17 85.76

1 14 79.73 3 29.86 1 30.00 1 29.89

E

2 28 317.95 30 176.65 26 176.79 28 176.67

1 10 77.02 11 53.02 12 77.01 13 76.88

F

2 10 77.02 11 53.02 12 77.01 13 76.88

1 25 156.12 26 152.16 4 47.21 4 47.07

G

2 26 156.12 26 152.16 4 47.21 4 47.07

1 15 86.46 17 84.85 16 86.42 15 84.85

H

2 16 86.46 17 84.85 16 86.42 15 84.85

1 5 49.68 8 49.40 14 82.58 8 49.40

I

2 21 108.71 23 108.43 23 133.80 23 108.43

1 18 101.00 21 101.67 21 100.73 21 100.75

J

2 17 101.00 21 101.67 21 100.73 21 100.75

1 22 119.79 7 47.80 7 47.92 7 47.77

L

2 27 177.48 6 46.73 6 47.56 6 47.42

1 6 57.53 9 53.02 8 57.52 9 57.39

M

2 6 57.53 9 53.02 8 57.52 9 57.39

1 19 101.00 19 101.67 19 100.73 19 100.75

O

2 20 101.00 19 101.67 19 100.73 19 100.75

1 1 7.54 1 8.87 27 232.47 29 222.31

Q

2 2 7.54 1 8.87 27 232.47 29 222.31

1 24 150.35 24 147.31 24 147.42 24 147.31

S

2 23 150.35 24 147.31 24 147.42 24 147.31

1 29 440.68 28 155.98 29 512.65 26 157.35

U

2 30 540.60 29 170.16 30 625.07 27 171.53

1 8 63.53 13 63.39 10 63.52 11 63.41

V

2 9 63.53 13 63.39 10 63.52 11 63.41

FNIR @ FPIR = 10−3

30 NA

29 NA

6 0.0020

2 0.0012

16 0.0043

7 0.0024

27 0.0591

27 0.0591

18 0.0062

14 0.0040

23 0.0203

24 0.0204

2 0.0012

1 0.0009

17 0.0049

11 0.0033

10 0.0031

11 0.0033

26 0.0543

25 0.0515

15 0.0041

13 0.0035

2 0.0012

2 0.0012

20 0.0108

21 0.0136

19 0.0099

22 0.0141

9 0.0027

7 0.0024

Table 63: Tabulation of storage and RAM requirements for Class B — Identification Flats, with an enrollment set size of 3 000 000 subjects. Letter refers

to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant

could make during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM refers to the

sum of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization

method. Reported RAM is the sum of the predicted RAM consumption returned from the enrollment method when enrolling images for the enrollment

set. Finalized Size is the amount of disk storage space used in the finalized enrollment set directory after the finalization method returned. Stored Size

is the actual amount of storage space used to hold the individual enrollment templates on disk, determined by summing the number of bytes written

by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise ranking, with the best performance

shaded in green and the worst in pink. For reference, the FNIR values from Table 13 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
158 FPVTE – FINGERPRINT MATCHING

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 9 92.86 11 96.24 10 92.63 11 96.33

C

2 10 92.86 11 96.24 10 92.63 11 96.33

1 16 132.37 19 155.88 19 159.68 19 159.37

D

2 15 132.37 18 153.13 18 156.93 18 156.62

1 14 127.39 3 57.47 1 57.71 1 57.52

E

2 28 573.25 30 318.66 26 318.89 28 318.70

1 7 90.93 6 82.27 6 90.92 7 90.70

F

2 6 90.93 6 82.27 6 90.92 7 90.70

1 25 274.35 26 267.49 4 82.40 4 82.17

G

2 26 274.35 26 267.49 4 82.40 4 82.17

1 17 144.02 16 142.06 14 143.97 16 142.06

H

2 18 144.02 16 142.06 14 143.97 16 142.06

1 4 84.42 10 83.96 16 144.38 6 83.96

I

2 11 110.22 13 109.76 17 153.35 13 109.76

1 20 181.00 22 182.11 20 182.47 22 180.58

J

2 21 181.00 23 182.11 23 182.47 23 180.58

1 23 192.19 4 72.47 2 72.67 2 72.43

L

2 27 274.95 4 72.47 3 72.67 2 72.43

1 5 90.93 8 82.27 8 90.92 9 90.70

M

2 8 90.93 8 82.27 8 90.92 9 90.70

1 19 181.00 20 182.11 21 182.47 20 180.58

O

2 22 181.00 20 182.11 21 182.47 20 180.58

1 2 13.33 1 15.77 27 412.86 29 395.06

Q

2 1 13.33 1 15.77 27 412.86 29 395.06

1 24 260.37 24 257.08 25 257.27 24 257.09

S

2 3 61.04 24 257.08 24 257.27 24 257.09

1 29 811.45 28 293.25 29 941.34 26 295.54

U

2 29 811.45 28 293.25 29 941.34 26 295.54

1 13 121.80 14 121.56 12 121.79 14 121.60

V

2 12 121.79 14 121.56 12 121.79 14 121.60

FNIR @ FPIR = 10−3

30 NA

24 0.0711

6 0.0015

2 0.0011

14 0.0088

13 0.0048

25 0.0734

25 0.0734

23 0.0368

20 0.0276

20 0.0276

19 0.0275

4 0.0013

1 0.0010

12 0.0047

10 0.0027

16 0.0102

15 0.0095

28 0.0934

27 0.0826

9 0.0025

10 0.0027

2 0.0011

4 0.0013

22 0.0311

29 0.1680

18 0.0163

17 0.0155

7 0.0024

7 0.0024

Table 64: Tabulation of storage and RAM requirements for Class C — Ten-Finger Plain-to-Plain, with an enrollment set size of 5 000 000 subjects. Letter

refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each

participant could make during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM

refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one

initialization method. Reported RAM is the sum of the predicted RAM consumption returned from the enrollment method when enrolling images for the

enrollment set. Finalized Size is the amount of disk storage space used in the finalized enrollment set directory after the finalization method returned.

Stored Size is the actual amount of storage space used to hold the individual enrollment templates on disk, determined by summing the number of

bytes written by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise ranking, with the best

performance shaded in green and the worst in pink. For reference, the FNIR values from Table 14 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 159

Participant RAM On Disk

Letter Sub. # Actual Reported Finalized Stored

1 14 183.36 14 190.50 14 183.11 14 190.59

C

2 15 183.36 14 190.50 14 183.11 14 190.59

1 10 132.40 22 302.53 18 303.52 24 303.21

D

2 9 132.37 27 309.65 19 310.65 25 310.33

1 16 191.66 3 95.45 1 95.69 1 95.50

E

2 30 930.48 30 528.40 26 528.63 28 528.45

1 7 130.29 5 118.45 4 130.29 5 130.07

F

2 6 130.29 5 118.45 4 130.29 5 130.07

1 20 261.29 18 254.66 2 97.99 2 97.76

G

2 19 261.29 18 254.66 2 97.99 2 97.76

1 13 144.02 10 143.46 8 143.97 10 143.46

H

2 12 144.02 10 143.46 8 143.97 10 143.46

1 4 113.80 4 113.34 12 153.41 4 113.34

I

2 11 137.03 9 136.57 13 153.69 9 136.57

1 22 303.13 24 304.24 21 355.15 21 302.68

J

2 24 303.13 23 304.24 20 355.15 20 302.68

1 21 280.49 12 151.41 10 151.61 12 151.37

L

2 26 367.82 12 151.41 11 151.61 12 151.37

1 8 130.29 7 118.45 6 130.29 7 130.07

M

2 5 130.29 7 118.45 6 130.29 7 130.07

1 25 303.13 25 304.24 22 355.15 22 302.68

O

2 23 303.13 25 304.24 22 355.15 22 302.68

1 1 20.22 1 25.61 27 666.73 29 641.13

Q

2 2 20.22 1 25.61 27 666.73 29 641.13

1 27 382.88 28 381.17 25 381.36 26 381.17

S

2 3 78.28 28 381.17 24 381.36 26 381.17

1 28 806.17 20 257.87 29 937.76 18 260.17

U

2 28 806.17 20 257.87 29 937.76 18 260.17

1 17 234.03 16 233.80 16 234.03 16 233.84

V

2 18 234.03 16 233.80 16 234.03 16 233.84

FNIR @ FPIR = 10−3

16 0.0094

15 0.0085

4 0.0015

7 0.0018

18 0.0106

12 0.0050

25 0.0536

25 0.0536

24 0.0447

21 0.0333

20 0.0201

19 0.0199

1 0.0013

2 0.0014

13 0.0051

9 0.0033

17 0.0097

14 0.0083

28 0.0783

27 0.0716

11 0.0034

9 0.0033

5 0.0017

2 0.0014

29 0.0860

30 0.2462

23 0.0358

22 0.0351

5 0.0017

8 0.0019

Table 65: Tabulation of storage and RAM requirements for Class C — Ten-Finger Rolled-to-Rolled, with an enrollment set size of 5 000 000 subjects. Letter

refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each

participant could make during the final submission period. All values are reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. Actual RAM

refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one

initialization method. Reported RAM is the sum of the predicted RAM consumption returned from the enrollment method when enrolling images for the

enrollment set. Finalized Size is the amount of disk storage space used in the finalized enrollment set directory after the finalization method returned.

Stored Size is the actual amount of storage space used to hold the individual enrollment templates on disk, determined by summing the number of

bytes written by the FpVTE test driver after each enrollment. The number to the left of a value provides the value’s column-wise ranking, with the best

performance shaded in green and the worst in pink. For reference, the FNIR values from Table 15 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
160 FPVTE – FINGERPRINT MATCHING

G Search Template Sizes

G.1 Mean Values

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 161

Participant Left Index Right Index Left and Right Index

Letter Sub. # Size FNIR Size FNIR Size FNIR

1 5 1.49 30 0.1335 5 1.51 30 0.1132 5 2.98 26 0.0368

C

2 5 1.49 31 0.1337 5 1.51 29 0.1124 5 2.98 28 0.0374

1 18 3.31 1 0.0197 18 3.34 1 0.0190 18 6.65 4 0.0030

D

2 18 3.31 1 0.0197 18 3.34 1 0.0190 18 6.65 4 0.0030

1 27 4.83 16 0.0745 27 4.89 15 0.0630 27 9.71 15 0.0207

E

2 27 4.83 15 0.0723 27 4.89 14 0.0624 27 9.71 14 0.0202

1 8 1.54 25 0.1111 8 1.55 25 0.0933 7 3.00 29 0.0386

F

2 8 1.54 22 0.1082 8 1.55 22 0.0903 7 3.00 30 0.0412

1 10 2.51 24 0.1089 10 2.52 24 0.0910 10 5.02 31 0.0515

G

2 10 2.51 23 0.1086 10 2.52 23 0.0909 10 5.02 20 0.0311

1 16 3.00 32 0.1576 16 3.00 32 0.1230 16 5.99 33 0.0686

H

2 16 3.00 33 0.1607 16 3.00 33 0.1249 16 5.99 32 0.0684

1 35 6.83 7 0.0257 35 6.87 5 0.0215 29 10.19 8 0.0058

I

2 36 10.07 8 0.0278 36 10.18 3 0.0214 36 20.17 4 0.0030

1 12 2.68 18 0.0786 12 2.72 20 0.0708 12 5.26 10 0.0143

J

2 12 2.68 14 0.0712 12 2.72 16 0.0643 12 5.26 10 0.0143

1 25 4.82 21 0.0883 25 4.85 18 0.0682 25 9.67 24 0.0360

K

2 25 4.82 20 0.0875 25 4.85 19 0.0685 25 9.67 19 0.0286

1 7 1.52 11 0.0625 7 1.53 12 0.0505 9 3.01 12 0.0146

L

2 22 4.47 9 0.0351 22 4.51 9 0.0295 22 8.93 9 0.0072

1 3 1.21 35 0.2995 3 1.18 36 0.2615 3 2.31 35 NA

M

2 3 1.21 34 0.2921 3 1.18 35 0.2526 3 2.31 34 NA

1 14 2.93 19 0.0818 14 2.98 21 0.0776 14 5.77 17 0.0229

O

2 14 2.93 17 0.0766 14 2.98 17 0.0675 14 5.77 16 0.0214

1 1 0.28 29 0.1308 1 0.28 31 0.1133 1 0.53 27 0.0370

P

2 1 0.28 28 0.1272 1 0.28 28 0.1100 1 0.53 21 0.0333

1 33 6.52 3 0.0222 33 6.57 6 0.0218 34 13.08 1 0.0027

Q

2 33 6.52 4 0.0226 33 6.57 3 0.0214 34 13.08 1 0.0027

1 23 4.74 10 0.0571 23 4.77 10 0.0442 23 9.52 18 0.0281

S

2 23 4.74 12 0.0650 23 4.77 11 0.0503 23 9.52 13 0.0195

1 31 6.00 36 NA 31 6.09 34 0.1929 32 12.09 36 NA

T

2 31 6.00 13 0.0685 31 6.09 13 0.0562 32 12.09 25 0.0366

1 29 5.17 27 0.1218 29 5.20 26 0.0996 30 10.36 22 0.0336

U

2 29 5.17 26 0.1178 29 5.20 27 0.1007 30 10.36 23 0.0358

1 20 3.70 6 0.0253 20 3.72 8 0.0223 20 7.41 7 0.0034

V

2 20 3.70 5 0.0252 20 3.72 7 0.0222 20 7.41 3 0.0028

Table 66: Tabulation of mean search template sizes for Class A. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. Size values indicate the mean kilobytes used to store a

search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA

indicates that the operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
162 FPVTE – FINGERPRINT MATCHING

Participant Left Slap Right Slap Left and Right Slap Identification Flats

Letter Sub. # Size FNIR Size FNIR Size FNIR Size FNIR

1 4 6.59 22 0.0654 4 6.70 24 0.0403 4 13.24 30 NA 2 16.13 30 NA

C

2 4 6.59 21 0.0647 4 6.70 23 0.0392 4 13.24 29 NA 2 16.13 29 NA1 16 11.27 6 0.0163 16 11.31 6 0.0072 16 22.39 6 0.0031 18 30.53 6 0.0020

D

2 15 11.18 5 0.0142 15 11.24 2 0.0052 15 22.24 5 0.0024 17 30.22 2 0.00121 1 3.88 13 0.0259 1 3.93 13 0.0151 1 7.78 15 0.0063 1 10.48 16 0.0043

E

2 28 23.22 7 0.0187 28 23.53 7 0.0083 28 46.65 10 0.0049 28 62.06 7 0.00241 11 9.66 29 0.1684 11 9.73 29 0.1222 11 19.21 28 0.0910 13 26.80 27 0.0591

F

2 11 9.66 28 0.1681 11 9.73 28 0.1220 11 19.21 26 0.0901 13 26.80 27 0.05911 13 10.25 18 0.0371 13 10.32 18 0.0212 13 20.53 18 0.0106 11 26.45 18 0.0062

G

2 13 10.25 17 0.0325 13 10.32 16 0.0198 13 20.53 17 0.0084 11 26.45 14 0.00401 17 11.92 23 0.0998 17 11.90 25 0.0641 17 23.77 23 0.0349 15 29.66 23 0.0203

H

2 17 11.92 24 0.1008 17 11.90 26 0.0647 17 23.77 24 0.0361 15 29.66 24 0.02041 10 8.92 4 0.0116 10 8.97 5 0.0058 8 14.37 3 0.0022 6 17.69 2 0.0012

I

2 23 14.25 1 0.0094 23 14.42 1 0.0045 23 28.60 1 0.0015 23 38.41 1 0.00091 21 12.76 15 0.0287 19 12.94 14 0.0156 21 25.51 16 0.0068 21 35.39 17 0.0049

J

2 21 12.76 10 0.0236 19 12.94 10 0.0126 21 25.51 9 0.0047 21 35.39 11 0.00331 3 6.08 16 0.0288 3 6.14 15 0.0167 3 12.15 12 0.0054 5 16.92 10 0.0031

L

2 2 6.02 14 0.0276 2 6.08 17 0.0202 2 12.03 14 0.0062 4 16.79 11 0.00331 6 7.08 30 0.1736 6 7.13 30 0.1259 6 14.11 27 0.0904 7 19.93 26 0.0543

M

2 6 7.08 27 0.1634 6 7.13 27 0.1155 6 14.11 25 0.0882 7 19.93 25 0.05151 19 12.76 12 0.0257 21 12.94 12 0.0142 19 25.51 13 0.0057 19 35.39 15 0.0041

O

2 19 12.76 11 0.0254 21 12.94 11 0.0132 19 25.51 11 0.0051 19 35.39 13 0.00351 29 29.00 2 0.0098 29 29.30 3 0.0057 29 58.19 2 0.0021 29 78.12 2 0.0012

Q

2 29 29.00 3 0.0099 29 29.30 3 0.0057 29 58.19 3 0.0022 29 78.12 2 0.00121 24 20.36 25 0.1089 24 20.56 21 0.0369 24 40.83 21 0.0160 24 51.62 20 0.0108

S

2 24 20.36 26 0.1133 24 20.56 22 0.0381 24 40.83 22 0.0190 24 51.62 21 0.01361 26 20.70 20 0.0500 26 20.73 19 0.0266 26 41.34 20 0.0139 26 55.81 19 0.0099

U

2 27 21.43 19 0.0461 27 21.60 20 0.0273 27 42.94 19 0.0124 27 60.97 22 0.01411 8 8.61 9 0.0192 8 8.65 8 0.0106 9 17.22 7 0.0036 9 22.27 9 0.0027

V

2 8 8.61 8 0.0190 8 8.65 9 0.0110 9 17.22 7 0.0036 9 22.27 7 0.0024

Table 67: Tabulation of mean search template sizes for Class B. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate betweenthe two submissions each participant could make. Size values indicate the mean kilobytes used to store a search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. TheFNIR column shows FNIR for each submission at FPIR = 10−3

. NA indicates that the operations required to produce the value could not be performed. The number to the left of a value

provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 163

Participant Ten-Finger Plain-to-Plain Ten-Finger Rolled-to-Rolled

Letter Sub. # Size FNIR Size FNIR

1 9 20.91 30 NA 14 40.15 16 0.0094

C

2 9 20.91 24 0.0711 14 40.15 15 0.0085

1 19 33.66 6 0.0015 24 63.63 4 0.0015

D

2 18 33.16 2 0.0011 25 65.36 7 0.0018

1 1 12.10 14 0.0088 1 19.95 18 0.0106

E

2 28 67.07 13 0.0048 28 110.22 12 0.0050

1 5 19.45 25 0.0734 3 27.41 25 0.0536

F

2 5 19.45 25 0.0734 3 27.41 25 0.0536

1 14 27.52 23 0.0368 10 30.76 24 0.0447

G

2 14 27.52 20 0.0276 10 30.76 21 0.0333

1 16 29.72 20 0.0276 8 29.96 20 0.0201

H

2 16 29.72 19 0.0275 8 29.96 19 0.0199

1 4 17.76 4 0.0013 2 23.76 1 0.0013

I

2 11 23.15 1 0.0010 7 28.49 2 0.0014

1 23 38.56 12 0.0047 23 63.60 13 0.0051

J

2 22 38.56 10 0.0027 20 63.60 9 0.0033

1 2 15.74 16 0.0102 12 32.38 17 0.0097

L

2 2 15.74 15 0.0095 12 32.38 14 0.0083

1 5 19.45 28 0.0934 3 27.41 28 0.0783

M

2 5 19.45 27 0.0826 3 27.41 27 0.0716

1 20 38.56 9 0.0025 21 63.60 11 0.0034

O

2 20 38.56 10 0.0027 21 63.60 9 0.0033

1 29 83.85 2 0.0011 29 134.42 5 0.0017

Q

2 29 83.85 4 0.0013 29 134.42 2 0.0014

1 24 54.12 22 0.0311 26 80.04 29 0.0860

S

2 24 54.12 29 0.1680 26 80.04 30 0.2462

1 26 62.80 18 0.0163 18 54.62 23 0.0358

U

2 26 62.80 17 0.0155 18 54.62 22 0.0351

1 12 25.78 7 0.0024 16 48.74 5 0.0017

V

2 12 25.78 7 0.0024 16 48.74 8 0.0019

Table 68: Tabulation of mean search template sizes for Class C. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. Size values indicate the mean kilobytes used to store a

search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA

indicates that the operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
164 FPVTE – FINGERPRINT MATCHING

G.2 Median Values

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 165

Participant Left Index Right Index Left and Right Index

Letter Sub. # Size FNIR Size FNIR Size FNIR

1 5 1.49 30 0.1335 5 1.51 30 0.1132 5 2.94 26 0.0368

C

2 5 1.49 31 0.1337 5 1.51 29 0.1124 5 2.94 28 0.0374

1 18 3.27 1 0.0197 18 3.30 1 0.0190 18 6.57 4 0.0030

D

2 18 3.27 1 0.0197 18 3.30 1 0.0190 18 6.57 4 0.0030

1 27 4.84 16 0.0745 27 4.91 15 0.0630 27 9.71 15 0.0207

E

2 27 4.84 15 0.0723 27 4.91 14 0.0624 27 9.71 14 0.0202

1 8 1.52 25 0.1111 8 1.53 25 0.0933 8 2.97 29 0.0386

F

2 8 1.52 22 0.1082 8 1.53 22 0.0903 8 2.97 30 0.0412

1 10 2.35 24 0.1089 10 2.36 24 0.0910 10 4.81 31 0.0515

G

2 10 2.35 23 0.1086 10 2.36 23 0.0909 10 4.81 20 0.0311

1 16 3.00 32 0.1576 16 3.00 32 0.1230 16 6.00 33 0.0686

H

2 16 3.00 33 0.1607 16 3.00 33 0.1249 16 6.00 32 0.0684

1 35 6.84 7 0.0257 35 6.88 5 0.0215 31 10.19 8 0.0058

I

2 36 10.02 8 0.0278 36 10.12 3 0.0214 36 20.05 4 0.0030

1 12 2.65 18 0.0786 12 2.68 20 0.0708 12 5.19 10 0.0143

J

2 12 2.65 14 0.0712 12 2.68 16 0.0643 12 5.19 10 0.0143

1 25 4.76 21 0.0883 25 4.79 18 0.0682 25 9.55 24 0.0360

K

2 25 4.76 20 0.0875 25 4.79 19 0.0685 25 9.55 19 0.0286

1 7 1.50 11 0.0625 7 1.51 12 0.0505 7 2.97 12 0.0146

L

2 22 4.41 9 0.0351 22 4.45 9 0.0295 22 8.81 9 0.0072

1 3 1.20 35 0.2995 3 1.17 36 0.2615 3 2.28 35 NA

M

2 3 1.20 34 0.2921 3 1.17 35 0.2526 3 2.28 34 NA

1 14 2.90 19 0.0818 14 2.94 21 0.0776 14 5.69 17 0.0229

O

2 14 2.90 17 0.0766 14 2.94 17 0.0675 14 5.69 16 0.0214

1 1 0.28 29 0.1308 1 0.28 31 0.1133 1 0.53 27 0.0370

P

2 1 0.28 28 0.1272 1 0.28 28 0.1100 1 0.53 21 0.0333

1 33 6.46 3 0.0222 33 6.51 6 0.0218 34 12.94 1 0.0027

Q

2 33 6.46 4 0.0226 33 6.51 3 0.0214 34 12.94 1 0.0027

1 23 4.69 10 0.0571 23 4.71 10 0.0442 23 9.40 18 0.0281

S

2 23 4.69 12 0.0650 23 4.71 11 0.0503 23 9.40 13 0.0195

1 31 5.81 36 NA 31 5.89 34 0.1929 32 11.73 36 NA

T

2 31 5.81 13 0.0685 31 5.89 13 0.0562 32 11.73 25 0.0366

1 29 5.01 27 0.1218 29 5.04 26 0.0996 29 10.05 22 0.0336

U

2 29 5.01 26 0.1178 29 5.04 27 0.1007 29 10.05 23 0.0358

1 20 3.63 6 0.0253 20 3.65 8 0.0223 20 7.27 7 0.0034

V

2 20 3.63 5 0.0252 20 3.65 7 0.0222 20 7.27 3 0.0028

Table 69: Tabulation of median search template sizes for Class A. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. Size values indicate the median kilobytes used to store a

search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA

indicates that the operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
166 FPVTE – FINGERPRINT MATCHING

Participant Left Slap Right Slap Left and Right Slap Identification Flats

Letter Sub. # Size FNIR Size FNIR Size FNIR Size FNIR

1 4 6.56 22 0.0654 4 6.67 24 0.0403 4 13.18 30 NA 2 16.03 30 NA

C

2 4 6.56 21 0.0647 4 6.67 23 0.0392 4 13.18 29 NA 2 16.03 29 NA1 16 11.30 6 0.0163 16 11.35 6 0.0072 16 22.48 6 0.0031 18 30.57 6 0.0020

D

2 15 11.18 5 0.0142 15 11.24 2 0.0052 15 22.24 5 0.0024 17 30.17 2 0.00121 1 3.89 13 0.0259 1 3.91 13 0.0151 1 7.78 15 0.0063 1 10.43 16 0.0043

E

2 28 23.35 7 0.0187 28 23.68 7 0.0083 28 46.93 10 0.0049 28 62.33 7 0.00241 11 9.41 29 0.1684 11 9.49 29 0.1222 11 18.78 28 0.0910 13 26.48 27 0.0591

F

2 11 9.41 28 0.1681 11 9.49 28 0.1220 11 18.78 26 0.0901 13 26.48 27 0.05911 13 9.99 18 0.0371 13 10.07 18 0.0212 13 20.12 18 0.0106 11 25.93 18 0.0062

G

2 13 9.99 17 0.0325 13 10.07 16 0.0198 13 20.12 17 0.0084 11 25.93 14 0.00401 17 12.00 23 0.0998 17 12.00 25 0.0641 17 24.00 23 0.0349 15 30.00 23 0.0203

H

2 17 12.00 24 0.1008 17 12.00 26 0.0647 17 24.00 24 0.0361 15 30.00 24 0.02041 10 9.00 4 0.0116 10 9.05 5 0.0058 8 14.52 3 0.0022 6 17.87 2 0.0012

I

2 23 14.26 1 0.0094 23 14.42 1 0.0045 23 28.63 1 0.0015 23 38.44 1 0.00091 19 12.73 15 0.0287 19 12.93 14 0.0156 19 25.46 16 0.0068 19 35.37 17 0.0049

J

2 19 12.73 10 0.0236 19 12.93 10 0.0126 19 25.46 9 0.0047 19 35.37 11 0.00331 3 6.06 16 0.0288 3 6.11 15 0.0167 3 12.12 12 0.0054 5 16.86 10 0.0031

L

2 2 6.00 14 0.0276 2 6.06 17 0.0202 2 12.00 14 0.0062 4 16.74 11 0.00331 6 6.91 30 0.1736 6 6.97 30 0.1259 6 13.82 27 0.0904 7 19.73 26 0.0543

M

2 6 6.91 27 0.1634 6 6.97 27 0.1155 6 13.82 25 0.0882 7 19.73 25 0.05151 19 12.73 12 0.0257 19 12.93 12 0.0142 19 25.46 13 0.0057 19 35.37 15 0.0041

O

2 19 12.73 11 0.0254 19 12.93 11 0.0132 19 25.46 11 0.0051 19 35.37 13 0.00351 29 29.00 2 0.0098 29 29.30 3 0.0057 29 58.20 2 0.0021 29 78.05 2 0.0012

Q

2 29 29.00 3 0.0099 29 29.30 3 0.0057 29 58.20 3 0.0022 29 78.05 2 0.00121 24 20.07 25 0.1089 24 20.25 21 0.0369 24 40.31 21 0.0160 24 51.27 20 0.0108

S

2 24 20.07 26 0.1133 24 20.25 22 0.0381 24 40.31 22 0.0190 24 51.27 21 0.01361 26 20.84 20 0.0500 26 20.92 19 0.0266 26 41.58 20 0.0139 26 56.14 19 0.0099

U

2 27 21.27 19 0.0461 27 21.43 20 0.0273 27 42.60 19 0.0124 27 60.55 22 0.01411 8 8.62 9 0.0192 8 8.66 8 0.0106 9 17.26 7 0.0036 9 22.46 9 0.0027

V

2 8 8.62 8 0.0190 8 8.66 9 0.0110 9 17.26 7 0.0036 9 22.46 7 0.0024

Table 70: Tabulation of median search template sizes for Class B. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate betweenthe two submissions each participant could make. Size values indicate the median kilobytes used to store a search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. TheFNIR column shows FNIR for each submission at FPIR = 10−3

. NA indicates that the operations required to produce the value could not be performed. The number to the left of a value

provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 167

Participant Ten-Finger Plain-to-Plain Ten-Finger Rolled-to-Rolled

Letter Sub. # Size FNIR Size FNIR

1 9 20.80 30 NA 14 40.13 16 0.0094

C

2 9 20.80 24 0.0711 14 40.13 15 0.0085

1 19 33.58 6 0.0015 20 63.49 4 0.0015

D

2 18 33.00 2 0.0011 25 65.19 7 0.0018

1 1 12.07 14 0.0088 1 19.69 18 0.0106

E

2 28 66.94 13 0.0048 28 108.80 12 0.0050

1 5 19.35 25 0.0734 3 27.48 25 0.0536

F

2 5 19.35 25 0.0734 3 27.48 25 0.0536

1 14 26.87 23 0.0368 10 30.12 24 0.0447

G

2 14 26.87 20 0.0276 10 30.12 21 0.0333

1 16 30.00 20 0.0276 8 30.00 20 0.0201

H

2 16 30.00 19 0.0275 8 30.00 19 0.0199

1 4 17.86 4 0.0013 2 23.92 1 0.0013

I

2 11 23.17 1 0.0010 7 28.90 2 0.0014

1 20 38.52 12 0.0047 21 63.55 13 0.0051

J

2 20 38.52 10 0.0027 21 63.55 9 0.0033

1 2 15.77 16 0.0102 12 32.65 17 0.0097

L

2 2 15.77 15 0.0095 12 32.65 14 0.0083

1 5 19.35 28 0.0934 3 27.48 28 0.0783

M

2 5 19.35 27 0.0826 3 27.48 27 0.0716

1 20 38.52 9 0.0025 21 63.55 11 0.0034

O

2 20 38.52 10 0.0027 21 63.55 9 0.0033

1 29 83.49 2 0.0011 29 135.01 5 0.0017

Q

2 29 83.49 4 0.0013 29 135.01 2 0.0014

1 24 53.59 22 0.0311 26 78.67 29 0.0860

S

2 24 53.59 29 0.1680 26 78.67 30 0.2462

1 26 63.23 18 0.0163 18 54.73 23 0.0358

U

2 26 63.23 17 0.0155 18 54.73 22 0.0351

1 12 25.68 7 0.0024 16 48.85 5 0.0017

V

2 12 25.68 7 0.0024 16 48.85 8 0.0019

Table 71: Tabulation of median search template sizes for Class C. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. Size values indicate the median kilobytes used to store a

search template on disk for a single subject, where 1 kB is equal to 1 024 bytes. The FNIR column shows FNIR for each submission at FPIR = 10−3. NA

indicates that the operations required to produce the value could not be performed. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
168 FPVTE – FINGERPRINT MATCHING

H Template Creation Times

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 169

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 21 0.45 19 0.41 19 0.41 19 0.39

C

2 21 0.45 19 0.41 19 0.41 19 0.39

1 35 1.79 34 1.46 35 1.57 34 1.43

D

2 34 1.79 33 1.46 34 1.55 33 1.42

1 11 0.37 15 0.36 15 0.35 15 0.35

E

2 11 0.37 15 0.36 15 0.35 15 0.35

1 31 1.21 31 1.13 29 1.11 29 1.07

F

2 31 1.21 31 1.13 29 1.11 29 1.07

1 19 0.43 21 0.41 21 0.57 23 0.55

G

2 19 0.43 21 0.41 21 0.57 23 0.55

1 13 0.37 7 0.31 11 0.33 7 0.30

H

2 13 0.37 7 0.31 11 0.33 7 0.30

1 33 1.49 35 1.47 33 1.48 35 1.46

I

2 36 2.29 36 2.20 36 2.19 36 2.15

1 7 0.35 13 0.34 9 0.33 13 0.32

J

2 7 0.35 13 0.34 9 0.33 13 0.32

1 27 1.09 27 1.07 27 1.06 27 1.05

K

2 27 1.09 27 1.07 27 1.06 27 1.05

1 1 0.07 1 0.06 1 0.07 1 0.05

L

2 4 0.19 4 0.16 4 0.17 4 0.15

1 29 1.21 29 1.13 31 1.12 31 1.07

M

2 29 1.21 29 1.13 31 1.12 31 1.07

1 5 0.29 5 0.28 5 0.28 5 0.27

O

2 5 0.29 5 0.28 5 0.28 5 0.27

1 17 0.42 17 0.38 17 0.38 17 0.36

P

2 17 0.42 17 0.38 17 0.38 17 0.36

1 23 0.64 23 0.56 23 0.57 21 0.54

Q

2 23 0.64 23 0.56 23 0.57 21 0.54

1 25 0.91 25 0.89 25 0.90 25 0.88

S

2 25 0.91 25 0.89 25 0.90 25 0.88

1 9 0.35 9 0.32 7 0.33 9 0.31

T

2 9 0.35 9 0.32 7 0.33 9 0.31

1 2 0.17 2 0.16 2 0.16 2 0.15

U

2 2 0.17 2 0.16 2 0.16 2 0.15

1 15 0.37 11 0.33 13 0.34 11 0.32

V

2 15 0.37 11 0.33 13 0.34 11 0.32

FNIR @ FPIR = 10−3

30 0.1335

31 0.1337

1 0.0197

1 0.0197

16 0.0745

15 0.0723

25 0.1111

22 0.1082

24 0.1089

23 0.1086

32 0.1576

33 0.1607

7 0.0257

8 0.0278

18 0.0786

14 0.0712

21 0.0883

20 0.0875

11 0.0625

9 0.0351

35 0.2995

34 0.2921

19 0.0818

17 0.0766

29 0.1308

28 0.1272

3 0.0222

4 0.0226

10 0.0571

12 0.0650

36 NA

13 0.0685

27 0.1218

26 0.1178

6 0.0253

5 0.0252

Table 72: Tabulation of enrollment time results for Class A — Left Index. Letter refers to the participant’s letter code found on the footer of this page. Sub.

# is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to create a fingerprint

template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are reported in

seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 7 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
170 FPVTE – FINGERPRINT MATCHING

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 21 0.45 19 0.41 19 0.41 19 0.39

C

2 21 0.45 19 0.41 19 0.41 19 0.39

1 34 1.78 33 1.45 35 1.58 34 1.43

D

2 35 1.80 34 1.46 34 1.57 33 1.43

1 13 0.37 15 0.37 15 0.37 15 0.36

E

2 13 0.37 15 0.37 15 0.37 15 0.36

1 29 1.23 29 1.15 31 1.14 29 1.09

F

2 29 1.23 29 1.15 31 1.14 29 1.09

1 19 0.43 21 0.41 21 0.57 23 0.55

G

2 19 0.43 21 0.41 21 0.57 23 0.55

1 15 0.38 7 0.31 9 0.34 7 0.30

H

2 15 0.38 7 0.31 9 0.34 7 0.30

1 33 1.51 35 1.48 33 1.49 35 1.46

I

2 36 2.29 36 2.20 36 2.19 36 2.15

1 7 0.35 13 0.33 11 0.34 13 0.33

J

2 7 0.35 13 0.33 11 0.34 13 0.33

1 27 1.09 27 1.06 27 1.06 27 1.05

K

2 27 1.09 27 1.06 27 1.06 27 1.05

1 1 0.07 1 0.06 1 0.07 1 0.05

L

2 4 0.19 4 0.16 4 0.17 4 0.16

1 31 1.24 31 1.16 29 1.14 31 1.09

M

2 31 1.24 31 1.16 29 1.14 31 1.09

1 5 0.29 5 0.28 5 0.28 5 0.27

O

2 5 0.29 5 0.28 5 0.28 5 0.27

1 17 0.42 17 0.38 17 0.39 17 0.37

P

2 17 0.42 17 0.38 17 0.39 17 0.37

1 23 0.64 23 0.56 23 0.58 21 0.54

Q

2 23 0.64 23 0.56 23 0.58 21 0.54

1 25 0.91 25 0.89 25 0.89 25 0.88

S

2 25 0.91 25 0.89 25 0.89 25 0.88

1 9 0.35 9 0.32 7 0.33 9 0.31

T

2 9 0.35 9 0.32 7 0.33 9 0.31

1 2 0.17 2 0.16 2 0.16 2 0.15

U

2 2 0.17 2 0.16 2 0.16 2 0.15

1 11 0.37 11 0.33 13 0.34 11 0.32

V

2 11 0.37 11 0.33 13 0.34 11 0.32

FNIR @ FPIR = 10−3

30 0.1132

29 0.1124

1 0.0190

1 0.0190

15 0.0630

14 0.0624

25 0.0933

22 0.0903

24 0.0910

23 0.0909

32 0.1230

33 0.1249

5 0.0215

3 0.0214

20 0.0708

16 0.0643

18 0.0682

19 0.0685

12 0.0505

9 0.0295

36 0.2615

35 0.2526

21 0.0776

17 0.0675

31 0.1133

28 0.1100

6 0.0218

3 0.0214

10 0.0442

11 0.0503

34 0.1929

13 0.0562

26 0.0996

27 0.1007

8 0.0223

7 0.0222

Table 73: Tabulation of enrollment time results for Class A — Right Index. Letter refers to the participant’s letter code found on the footer of this page. Sub.

# is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to create a fingerprint

template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are reported in

seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 8 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 171

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 21 0.88 21 0.80 19 0.80 19 0.78

C

2 21 0.88 21 0.80 19 0.80 19 0.78

1 35 3.57 34 2.91 34 3.10 33 2.84

D

2 34 3.55 33 2.89 35 3.12 34 2.84

1 15 0.74 15 0.73 15 0.70 15 0.70

E

2 15 0.74 15 0.73 15 0.70 15 0.70

1 29 2.42 29 2.26 29 2.23 29 2.15

F

2 29 2.42 29 2.26 29 2.23 29 2.15

1 19 0.84 19 0.80 21 1.13 23 1.09

G

2 19 0.84 19 0.80 21 1.13 23 1.09

1 13 0.74 7 0.62 9 0.66 7 0.60

H

2 13 0.74 7 0.62 9 0.66 7 0.60

1 33 2.98 35 2.96 33 2.96 35 2.93

I

2 36 4.59 36 4.40 36 4.37 36 4.30

1 7 0.69 13 0.67 11 0.66 13 0.65

J

2 7 0.69 13 0.67 11 0.66 13 0.65

1 27 2.17 27 2.13 27 2.11 27 2.09

K

2 27 2.17 27 2.13 27 2.11 27 2.09

1 1 0.12 1 0.11 1 0.11 1 0.11

L

2 4 0.36 4 0.32 4 0.33 4 0.31

1 31 2.42 31 2.27 31 2.25 31 2.16

M

2 31 2.42 31 2.27 31 2.25 31 2.16

1 5 0.57 5 0.55 5 0.55 5 0.53

O

2 5 0.57 5 0.55 5 0.55 5 0.53

1 17 0.83 17 0.76 17 0.77 17 0.72

P

2 17 0.83 17 0.76 17 0.77 17 0.72

1 23 1.27 23 1.10 23 1.13 21 1.08

Q

2 23 1.27 23 1.10 23 1.13 21 1.08

1 25 1.81 25 1.78 25 1.77 25 1.75

S

2 25 1.81 25 1.78 25 1.77 25 1.75

1 9 0.70 9 0.64 7 0.65 9 0.62

T

2 9 0.70 9 0.64 7 0.65 9 0.62

1 2 0.32 2 0.31 2 0.30 2 0.30

U

2 2 0.32 2 0.31 2 0.30 2 0.30

1 11 0.73 11 0.65 13 0.68 11 0.64

V

2 11 0.73 11 0.65 13 0.68 11 0.64

FNIR @ FPIR = 10−3

26 0.0368

28 0.0374

4 0.0030

4 0.0030

15 0.0207

14 0.0202

29 0.0386

30 0.0412

31 0.0515

20 0.0311

33 0.0686

32 0.0684

8 0.0058

4 0.0030

10 0.0143

10 0.0143

24 0.0360

19 0.0286

12 0.0146

9 0.0072

35 NA

34 NA

17 0.0229

16 0.0214

27 0.0370

21 0.0333

1 0.0027

1 0.0027

18 0.0281

13 0.0195

36 NA

25 0.0366

22 0.0336

23 0.0358

7 0.0034

3 0.0028

Table 74: Tabulation of enrollment time results for Class A — Left and Right Index. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to create a

fingerprint template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are reported

in seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 9 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
172 FPVTE – FINGERPRINT MATCHING

Participant Search

Letter Sub. # Mean Median

1 12 2.13 12 2.12

C

2 12 2.13 12 2.12

1 14 2.16 14 2.15

D

2 24 4.18 24 4.17

1 11 1.95 11 1.95

E

2 15 2.21 15 2.21

1 28 6.94 26 6.73

F

2 28 6.94 26 6.73

1 18 2.81 18 2.83

G

2 18 2.81 18 2.83

1 9 1.68 9 1.67

H

2 9 1.68 9 1.67

1 25 6.50 25 6.50

I

2 30 7.68 30 7.67

1 7 1.22 3 1.21

J

2 7 1.22 3 1.21

1 2 1.13 2 1.11

L

2 1 0.33 1 0.33

1 26 6.94 28 6.73

M

2 26 6.94 28 6.73

1 5 1.22 5 1.21

O

2 5 1.22 5 1.21

1 20 3.41 20 3.41

Q

2 20 3.41 20 3.41

1 22 3.97 22 3.96

S

2 22 3.97 22 3.96

1 17 2.46 17 2.42

U

2 16 2.45 16 2.41

1 3 1.21 7 1.22

V

2 3 1.21 7 1.22

FNIR @ FPIR = 10−3

22 0.0654

21 0.0647

6 0.0163

5 0.0142

13 0.0259

7 0.0187

29 0.1684

28 0.1681

18 0.0371

17 0.0325

23 0.0998

24 0.1008

4 0.0116

1 0.0094

15 0.0287

10 0.0236

16 0.0288

14 0.0276

30 0.1736

27 0.1634

12 0.0257

11 0.0254

2 0.0098

3 0.0099

25 0.1089

26 0.1133

20 0.0500

19 0.0461

9 0.0192

8 0.0190

Table 75: Tabulation of enrollment time results for Class B — Left Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. #

is an identifier used to differentiate between the two submissions each participant could make. Search shows the time used to create a search template to

be used for a query. All values are reported in seconds, but were originally recorded to microsecond precision. The number to the left of a value provides

the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 10 are

reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 173

Participant Search

Letter Sub. # Mean Median

1 12 2.10 12 2.09

C

2 12 2.10 12 2.09

1 14 2.15 14 2.14

D

2 24 4.15 24 4.13

1 11 1.92 11 1.91

E

2 15 2.18 15 2.18

1 26 6.86 26 6.68

F

2 26 6.86 26 6.68

1 18 2.76 18 2.78

G

2 18 2.76 18 2.78

1 9 1.64 9 1.63

H

2 9 1.64 9 1.63

1 25 6.47 25 6.47

I

2 30 7.65 30 7.65

1 5 1.21 5 1.20

J

2 5 1.21 5 1.20

1 2 1.12 2 1.11

L

2 1 0.33 1 0.33

1 28 6.88 28 6.69

M

2 28 6.88 28 6.69

1 7 1.21 7 1.20

O

2 7 1.21 7 1.20

1 20 3.41 20 3.41

Q

2 20 3.41 20 3.41

1 22 3.89 22 3.88

S

2 22 3.89 22 3.88

1 16 2.43 16 2.39

U

2 17 2.43 17 2.39

1 3 1.19 3 1.19

V

2 3 1.19 3 1.19

FNIR @ FPIR = 10−3

24 0.0403

23 0.0392

6 0.0072

2 0.0052

13 0.0151

7 0.0083

29 0.1222

28 0.1220

18 0.0212

16 0.0198

25 0.0641

26 0.0647

5 0.0058

1 0.0045

14 0.0156

10 0.0126

15 0.0167

17 0.0202

30 0.1259

27 0.1155

12 0.0142

11 0.0132

3 0.0057

3 0.0057

21 0.0369

22 0.0381

19 0.0266

20 0.0273

8 0.0106

9 0.0110

Table 76: Tabulation of enrollment time results for Class B — Right Slap. Letter refers to the participant’s letter code found on the footer of this page.

Sub. # is an identifier used to differentiate between the two submissions each participant could make. Search shows the time used to create a search

template to be used for a query. All values are reported in seconds, but were originally recorded to microsecond precision. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from

Table 11 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
174 FPVTE – FINGERPRINT MATCHING

Participant Search

Letter Sub. # Mean Median

1 12 4.22 12 4.20

C

2 12 4.22 12 4.20

1 14 4.29 14 4.28

D

2 24 8.31 24 8.28

1 11 3.86 11 3.85

E

2 15 4.39 15 4.38

1 26 13.78 26 13.49

F

2 26 13.78 26 13.49

1 18 5.59 18 5.62

G

2 18 5.59 18 5.62

1 9 3.31 9 3.31

H

2 9 3.31 9 3.31

1 25 12.94 25 12.96

I

2 30 15.30 30 15.33

1 7 2.42 5 2.40

J

2 7 2.42 5 2.40

1 2 2.24 2 2.23

L

2 1 0.66 1 0.66

1 28 13.79 28 13.53

M

2 28 13.79 28 13.53

1 5 2.42 3 2.40

O

2 5 2.42 3 2.40

1 20 6.84 20 6.84

Q

2 20 6.84 20 6.84

1 22 7.82 22 7.83

S

2 22 7.82 22 7.83

1 17 4.91 16 4.82

U

2 16 4.89 17 4.83

1 3 2.40 7 2.40

V

2 3 2.40 7 2.40

FNIR @ FPIR = 10−3

30 NA

29 NA

6 0.0031

5 0.0024

15 0.0063

10 0.0049

28 0.0910

26 0.0901

18 0.0106

17 0.0084

23 0.0349

24 0.0361

3 0.0022

1 0.0015

16 0.0068

9 0.0047

12 0.0054

14 0.0062

27 0.0904

25 0.0882

13 0.0057

11 0.0051

2 0.0021

3 0.0022

21 0.0160

22 0.0190

20 0.0139

19 0.0124

7 0.0036

7 0.0036

Table 77: Tabulation of enrollment time results for Class B — Left and Right Slap. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Search shows the time used to create a search

template to be used for a query. All values are reported in seconds, but were originally recorded to microsecond precision. The number to the left of a

value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. For reference, the FNIR values from

Table 12 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 175

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 11 4.92 11 5.06 11 5.16 11 5.13

C

2 11 4.92 11 5.06 11 5.16 11 5.13

1 19 5.82 19 5.97 17 6.19 17 6.16

D

2 24 11.20 24 11.47 24 11.90 24 11.86

1 13 5.11 13 5.28 13 5.35 13 5.34

E

2 18 5.69 18 5.89 16 5.95 16 5.93

1 28 17.69 28 17.86 28 18.36 26 18.07

F

2 28 17.69 28 17.86 28 18.36 26 18.07

1 14 5.41 14 5.60 18 7.89 18 7.90

G

2 14 5.41 14 5.60 18 7.89 18 7.90

1 9 4.15 9 4.28 9 4.37 9 4.37

H

2 9 4.15 9 4.28 9 4.37 9 4.37

1 25 15.80 25 16.47 25 16.50 25 16.52

I

2 30 18.56 30 19.35 30 19.36 30 19.36

1 3 3.20 3 3.27 7 3.38 3 3.35

J

2 3 3.20 3 3.27 7 3.38 3 3.35

1 2 2.94 2 3.02 2 3.05 2 3.05

L

2 1 0.84 1 0.87 1 0.88 1 0.88

1 26 17.66 26 17.85 26 18.36 28 18.11

M

2 26 17.66 26 17.85 26 18.36 28 18.11

1 7 3.20 5 3.27 5 3.38 5 3.36

O

2 7 3.20 5 3.27 5 3.38 5 3.36

1 20 8.50 20 8.85 20 8.89 20 8.92

Q

2 20 8.50 20 8.85 20 8.89 20 8.92

1 22 9.80 22 10.19 22 10.24 22 10.31

S

2 22 9.80 22 10.19 22 10.24 22 10.31

1 17 5.66 17 5.73 15 5.90 15 5.82

U

2 16 5.56 16 5.66 14 5.80 14 5.73

1 5 3.20 7 3.30 3 3.35 7 3.36

V

2 5 3.20 7 3.30 3 3.35 7 3.36

FNIR @ FPIR = 10−3

30 NA

29 NA

6 0.0020

2 0.0012

16 0.0043

7 0.0024

27 0.0591

27 0.0591

18 0.0062

14 0.0040

23 0.0203

24 0.0204

2 0.0012

1 0.0009

17 0.0049

11 0.0033

10 0.0031

11 0.0033

26 0.0543

25 0.0515

15 0.0041

13 0.0035

2 0.0012

2 0.0012

20 0.0108

21 0.0136

19 0.0099

22 0.0141

9 0.0027

7 0.0024

Table 78: Tabulation of enrollment time results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to create a

fingerprint template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are reported

in seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 13 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
176 FPVTE – FINGERPRINT MATCHING

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 15 5.93 13 5.89 13 5.84 13 5.80

C

2 15 5.93 13 5.89 13 5.84 13 5.80

1 19 7.10 19 7.09 17 7.12 17 7.10

D

2 24 13.55 24 13.52 24 13.69 24 13.66

1 11 5.19 11 5.21 11 5.20 11 5.20

E

2 12 5.20 12 5.22 12 5.21 12 5.20

1 27 15.96 25 15.88 27 15.96 27 15.87

F

2 27 15.96 25 15.88 27 15.96 27 15.87

1 13 5.93 15 5.91 18 8.35 18 8.32

G

2 13 5.93 15 5.91 18 8.35 18 8.32

1 9 5.18 9 5.21 9 5.16 9 5.16

H

2 9 5.18 9 5.21 9 5.16 9 5.16

1 29 16.65 29 16.67 29 16.71 29 16.67

I

2 30 17.15 30 17.07 30 17.04 30 16.99

1 3 3.61 3 3.58 3 3.62 5 3.62

J

2 6 3.63 6 3.60 6 3.64 6 3.62

1 1 3.56 1 3.52 1 3.51 1 3.48

L

2 1 3.56 1 3.52 1 3.51 1 3.48

1 25 15.95 27 15.89 25 15.91 25 15.83

M

2 25 15.95 27 15.89 25 15.91 25 15.83

1 4 3.63 4 3.60 4 3.63 3 3.61

O

2 4 3.63 4 3.60 4 3.63 3 3.61

1 20 9.10 20 9.08 20 9.14 20 9.11

Q

2 20 9.10 20 9.08 20 9.14 20 9.11

1 22 10.86 22 10.87 22 10.91 22 10.87

S

2 22 10.86 22 10.87 22 10.91 22 10.87

1 17 6.34 17 6.09 15 6.13 15 5.91

U

2 17 6.34 17 6.09 15 6.13 15 5.91

1 7 3.68 7 3.67 7 3.69 7 3.66

V

2 7 3.68 7 3.67 7 3.69 7 3.66

FNIR @ FPIR = 10−3

30 NA

24 0.0711

6 0.0015

2 0.0011

14 0.0088

13 0.0048

25 0.0734

25 0.0734

23 0.0368

20 0.0276

20 0.0276

19 0.0275

4 0.0013

1 0.0010

12 0.0047

10 0.0027

16 0.0102

15 0.0095

28 0.0934

27 0.0826

9 0.0025

10 0.0027

2 0.0011

4 0.0013

22 0.0311

29 0.1680

18 0.0163

17 0.0155

7 0.0024

7 0.0024

Table 79: Tabulation of enrollment time results for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s letter code found on the footer

of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to

create a fingerprint template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are

reported in seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking,

with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 14 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 177

Participant Enrollment Search

Letter Sub. # Mean Median Mean Median

1 13 11.18 13 11.00 13 10.79 13 10.69

C

2 13 11.18 13 11.00 13 10.79 13 10.69

1 21 17.37 21 17.27 23 17.44 21 17.39

D

2 30 30.78 30 30.70 30 30.43 30 30.47

1 12 9.93 12 9.94 12 9.90 12 9.92

E

2 11 9.92 11 9.94 11 9.89 11 9.91

1 26 21.06 28 20.95 28 21.07 28 20.92

F

2 26 21.06 28 20.95 28 21.07 28 20.92

1 15 11.21 15 11.19 19 15.55 19 15.50

G

2 15 11.21 15 11.19 19 15.55 19 15.50

1 17 12.36 17 12.36 15 12.08 15 12.17

H

2 17 12.36 17 12.36 15 12.08 15 12.17

1 25 20.25 25 20.25 25 20.21 25 20.23

I

2 24 18.75 24 18.76 24 18.72 24 18.73

1 7 6.78 5 6.67 5 6.78 5 6.69

J

2 8 6.80 8 6.71 8 6.82 8 6.74

1 3 4.43 3 4.44 3 4.36 3 4.36

L

2 3 4.43 3 4.44 3 4.36 3 4.36

1 28 21.08 26 20.92 26 21.02 26 20.89

M

2 28 21.08 26 20.92 26 21.02 26 20.89

1 5 6.77 6 6.67 6 6.80 6 6.71

O

2 5 6.77 6 6.67 6 6.80 6 6.71

1 19 12.94 19 13.03 17 12.95 17 13.06

Q

2 19 12.94 19 13.03 17 12.95 17 13.06

1 22 17.54 22 17.67 21 17.43 22 17.57

S

2 22 17.54 22 17.67 21 17.43 22 17.57

1 1 2.95 1 2.88 1 2.94 1 2.87

U

2 1 2.95 1 2.88 1 2.94 1 2.87

1 9 8.60 9 8.62 9 8.48 9 8.50

V

2 9 8.60 9 8.62 9 8.48 9 8.50

FNIR @ FPIR = 10−3

16 0.0094

15 0.0085

4 0.0015

7 0.0018

18 0.0106

12 0.0050

25 0.0536

25 0.0536

24 0.0447

21 0.0333

20 0.0201

19 0.0199

1 0.0013

2 0.0014

13 0.0051

9 0.0033

17 0.0097

14 0.0083

28 0.0783

27 0.0716

11 0.0034

9 0.0033

5 0.0017

2 0.0014

29 0.0860

30 0.2462

23 0.0358

22 0.0351

5 0.0017

8 0.0019

Table 80: Tabulation of enrollment time results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on the footer

of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Enrollment shows the time used to

create a fingerprint template to be used in an enrollment set. Search shows the time used to create a search template to be used for a query. All values are

reported in seconds, but were originally recorded to microsecond precision. The number to the left of a value provides the value’s column-wise ranking,

with the best performance shaded in green and the worst in pink. For reference, the FNIR values from Table 15 are reprinted to the right of this table.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
178 FPVTE – FINGERPRINT MATCHING

I Ranked Results

In order to reduce the number of tables in Section 10 of the main body of the report, this appendix contains the tables

showing ranked results for all three classes. The tables from the main body of the document are repeated in this appendix

so there is a complete set of tables here for the reader to analyze.

Class A results are in Tables 81 through 83, Class B results are in Tables 84 through 87, and Class C results are in Tables 88

through 89.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 179

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

< 20 seconds

D 1 1 0.0197 20 7.52 20 7.32 30 1.57 29 1.43 19 0.61

Q 1 2 0.0222 29 15.90 28 15.70 20 0.57 19 0.54 13 0.34

Q 2 3 0.0226 23 10.42 24 10.43 20 0.57 19 0.54 14 0.34

V 1 4 0.0253 19 6.22 19 6.01 12 0.34 10 0.32 17 0.39

I 1 5 0.0257 22 10.36 22 9.94 29 1.48 30 1.46 20 0.70

L 2 6 0.0351 12 3.34 12 3.32 3 0.17 3 0.15 28 2.32

S 1 7 0.0571 28 15.37 29 16.86 22 0.90 22 0.88 21 0.72

L 1 8 0.0625 2 0.30 2 0.29 1 0.07 1 0.05 26 1.14

T 2 9 0.0685 18 5.96 18 5.97 6 0.33 8 0.31 1 0.01

J 2 10 0.0712 7 1.34 7 1.25 8 0.33 11 0.32 9 0.32

E 2 11 0.0723 30 16.71 30 16.90 13 0.35 13 0.35 24 1.11

E 1 12 0.0745 4 0.57 3 0.35 13 0.35 13 0.35 25 1.12

O 2 13 0.0766 9 1.63 9 1.56 4 0.28 4 0.27 15 0.35

J 1 14 0.0786 3 0.56 4 0.54 8 0.33 11 0.32 9 0.32

O 1 15 0.0818 5 0.64 5 0.62 4 0.28 4 0.27 15 0.35

K 2 16 0.0875 24 10.47 23 10.32 23 1.06 23 1.05 30 3.87

K 1 17 0.0883 25 10.48 25 10.44 23 1.06 23 1.05 29 3.87

F 2 18 0.1082 15 3.78 14 3.56 25 1.11 25 1.07 5 0.18

G 1 19 0.1089 21 9.52 21 9.74 19 0.57 21 0.55 18 0.57

F 1 20 0.1111 11 2.52 11 2.49 25 1.11 25 1.07 6 0.18

U 1 21 0.1218 26 14.72 27 14.42 2 0.16 2 0.15 27 1.70

P 2 22 0.1272 13 3.43 13 3.33 15 0.38 15 0.36 22 0.78

P 1 23 0.1308 8 1.38 8 1.32 15 0.38 15 0.36 23 0.78

C 1 24 0.1335 1 0.29 1 0.26 17 0.41 17 0.39 7 0.18

C 2 25 0.1337 6 0.87 6 0.76 17 0.41 17 0.39 8 0.18

H 1 26 0.1576 14 3.65 15 3.61 10 0.33 6 0.30 11 0.33

H 2 27 0.1607 17 4.26 17 4.13 10 0.33 6 0.30 11 0.33

M 2 28 0.2921 27 15.19 26 10.70 27 1.12 27 1.07 4 0.14

M 1 29 0.2995 10 2.07 10 1.84 27 1.12 27 1.07 3 0.14

T 1 30 NA 16 4.18 16 3.99 6 0.33 8 0.31 2 0.01

≥ 20 seconds

D 2 1 0.0197 2 42.64 3 41.84 5 1.55 5 1.42 3 0.61

V 2 2 0.0252 6 66.23 6 65.35 2 0.34 2 0.32 1 0.39

I 2 3 0.0278 3 43.24 2 40.99 6 2.19 6 2.15 5 1.04

S 2 4 0.0650 4 45.59 4 44.66 4 0.90 4 0.88 4 0.72

G 2 5 0.1086 5 54.24 5 54.03 3 0.57 3 0.55 2 0.57

U 2 6 0.1178 1 25.66 1 24.16 1 0.16 1 0.15 6 1.42

Table 81: Tabulation of ranked results for Class A — Left Index. Submissions were split into two groups. The first group includes submissions that

performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The FNIR column was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value

could not be performed. The Identification column shows the time used to perform a search over an enrollment set of 100 000, as seen in Table 17. The

Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 72. Identification and Search Enrollment

durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage

one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in Table 60. RAM is

reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
180 FPVTE – FINGERPRINT MATCHING

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

< 20 seconds

D 1 1 0.0190 20 7.68 20 7.46 30 1.58 29 1.43 19 0.61

Q 2 2 0.0214 22 10.15 23 9.98 20 0.58 19 0.54 11 0.33

I 1 3 0.0215 23 10.19 22 9.83 29 1.49 30 1.46 20 0.69

Q 1 4 0.0218 28 14.44 28 14.24 20 0.58 19 0.54 11 0.33

V 1 5 0.0223 19 5.95 18 5.60 12 0.34 10 0.32 17 0.39

L 2 6 0.0295 12 3.26 13 3.26 3 0.17 3 0.16 28 2.32

S 1 7 0.0442 29 15.08 30 16.55 22 0.89 22 0.88 21 0.71

L 1 8 0.0505 2 0.29 2 0.26 1 0.07 1 0.05 26 1.14

T 2 9 0.0562 18 5.64 19 5.87 6 0.33 8 0.31 1 0.01

E 2 10 0.0624 30 15.89 29 16.27 13 0.37 13 0.36 25 1.07

E 1 11 0.0630 3 0.45 3 0.32 13 0.37 13 0.36 24 1.07

J 2 12 0.0643 7 1.25 7 1.13 10 0.34 11 0.33 9 0.31

O 2 13 0.0675 9 1.48 9 1.36 4 0.28 4 0.27 16 0.34

K 1 14 0.0682 25 10.42 26 10.42 23 1.06 23 1.05 30 3.87

K 2 15 0.0685 24 10.30 25 10.27 23 1.06 23 1.05 29 3.87

J 1 16 0.0708 4 0.53 4 0.51 10 0.34 11 0.33 10 0.31

O 1 17 0.0776 5 0.59 5 0.56 4 0.28 4 0.27 15 0.34

F 2 18 0.0903 15 3.71 15 3.60 27 1.14 25 1.09 5 0.17

G 1 19 0.0910 21 10.12 24 10.10 19 0.57 21 0.55 18 0.57

F 1 20 0.0933 11 2.52 11 2.38 27 1.14 25 1.09 6 0.17

U 1 21 0.0996 27 12.02 27 10.76 2 0.16 2 0.15 27 1.56

P 2 22 0.1100 13 3.49 12 3.07 15 0.39 15 0.37 23 0.76

C 2 23 0.1124 6 0.76 6 0.69 17 0.41 17 0.39 8 0.18

C 1 24 0.1132 1 0.25 1 0.24 17 0.41 17 0.39 7 0.17

P 1 25 0.1133 8 1.38 8 1.24 15 0.39 15 0.37 22 0.76

H 1 26 0.1230 14 3.58 14 3.56 8 0.34 6 0.30 14 0.33

H 2 27 0.1249 17 4.13 17 4.05 8 0.34 6 0.30 13 0.33

T 1 28 0.1929 16 3.82 16 3.73 6 0.33 8 0.31 1 0.01

M 2 29 0.2526 26 11.31 21 9.39 25 1.14 27 1.09 3 0.14

M 1 30 0.2615 10 1.75 10 1.78 25 1.14 27 1.09 3 0.14

≥ 20 seconds

D 2 1 0.0190 2 29.26 2 28.64 5 1.57 5 1.43 3 0.61

I 2 2 0.0214 3 41.60 3 40.35 6 2.19 6 2.15 5 1.01

V 2 3 0.0222 6 64.47 6 61.24 2 0.34 2 0.32 1 0.39

S 2 4 0.0503 4 43.56 4 46.05 4 0.89 4 0.88 4 0.71

G 2 5 0.0909 5 57.88 5 59.55 3 0.57 3 0.55 2 0.57

U 2 6 0.1007 1 22.39 1 20.10 1 0.16 1 0.15 6 1.30

Table 82: Tabulation of ranked results for Class A — Right Index. Submissions were split into two groups. The first group includes submissions that

performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The FNIR column was computed at the score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search

over an enrollment set of 100 000, as seen in Table 17. The Search Enrollment column shows the time used to create a search template to be used for a

query, as seen in Table 73. Identification and Search Enrollment durations are reported in seconds, but were originally recorded to microsecond precision.

RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification

stage one initialization method, as seen in Table 61. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of

a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on the FNIR

column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 181

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

< 20 seconds

V 1 1 0.0034 5 9.50 5 9.29 4 0.68 3 0.64 5 11.77

I 1 2 0.0058 9 18.92 8 17.87 9 2.96 9 2.93 6 15.83

J 1 3 0.0143 6 14.00 6 13.64 3 0.66 4 0.65 3 8.30

L 1 4 0.0146 1 2.20 2 2.19 1 0.11 1 0.11 8 18.76

O 1 5 0.0229 7 15.34 7 14.46 2 0.55 2 0.53 4 9.05

K 1 6 0.0360 8 18.32 9 18.01 8 2.11 8 2.09 9 61.81

C 1 7 0.0368 2 2.39 1 2.08 5 0.80 5 0.78 2 4.87

C 2 8 0.0374 4 6.34 4 6.35 5 0.80 5 0.78 1 4.87

G 1 9 0.0515 3 6.27 3 5.22 7 1.13 7 1.09 7 16.38

≥ 20 seconds

Q 1 1 0.0027 21 213.08 21 212.69 16 1.13 15 1.08 10 9.14

Q 2 1 0.0027 19 163.65 19 161.02 16 1.13 15 1.08 9 9.14

V 2 3 0.0028 18 133.45 18 127.65 10 0.68 9 0.64 13 11.77

I 2 4 0.0030 25 385.14 25 338.88 27 4.37 27 4.30 21 30.83

D 2 4 0.0030 23 234.52 23 237.43 26 3.12 26 2.84 17 18.58

D 1 4 0.0030 16 73.01 15 70.99 25 3.10 25 2.84 17 18.58

L 2 7 0.0072 3 23.54 3 23.42 3 0.33 3 0.31 26 53.98

J 2 8 0.0143 7 36.19 7 33.35 9 0.66 10 0.65 7 8.30

S 2 9 0.0195 26 429.02 26 495.50 18 1.77 18 1.75 14 14.82

E 2 10 0.0202 27 500.30 27 518.11 11 0.70 11 0.70 23 33.41

E 1 11 0.0207 2 22.27 1 16.35 11 0.70 11 0.70 22 33.40

O 2 12 0.0214 10 45.52 10 43.53 4 0.55 4 0.53 8 9.05

S 1 13 0.0281 1 20.11 2 23.00 18 1.77 18 1.75 14 14.82

K 2 14 0.0286 6 32.68 6 32.93 20 2.11 20 2.09 27 61.81

G 2 15 0.0311 22 227.27 22 221.16 15 1.13 17 1.09 16 16.38

P 2 16 0.0333 17 114.37 17 101.16 13 0.77 13 0.72 19 21.41

U 1 17 0.0336 11 47.60 11 45.51 1 0.30 1 0.30 25 44.63

U 2 18 0.0358 24 252.04 24 240.40 1 0.30 1 0.30 24 37.35

T 2 19 0.0366 9 38.91 9 37.23 5 0.65 7 0.62 1 0.01

P 1 20 0.0370 14 63.41 14 63.65 13 0.77 13 0.72 20 21.42

F 1 21 0.0386 13 59.30 13 60.66 21 2.23 21 2.15 5 4.86

F 2 22 0.0412 15 71.45 16 73.95 21 2.23 21 2.15 5 4.86

H 2 23 0.0684 12 53.77 12 52.25 7 0.66 5 0.60 11 9.36

H 1 24 0.0686 8 37.65 8 36.71 7 0.66 5 0.60 12 9.36

M 2 25 NA 20 183.20 20 171.24 23 2.25 23 2.16 4 3.76

M 1 26 NA 5 32.59 5 31.44 23 2.25 23 2.16 3 3.75

T 1 27 NA 4 26.96 4 25.68 5 0.65 7 0.62 1 0.01

Table 83: Tabulation of ranked results for Class A — Left and Right Index. Submissions were split into two groups. The first group includes submissions

that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer. Letter refers to the

participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could

make. The FNIR column was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value

could not be performed. The Identification column shows the time used to perform a search over an enrollment set of 1 600 000, as seen in Table 18. The

Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 74. Identification and Search Enrollment

durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage

one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in Table 62. RAM is

reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
182 FPVTE – FINGERPRINT MATCHING

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0094 18 51.59 13 38.26 30 7.68 30 7.67 21 108.71

Q 1 2 0.0098 17 51.33 19 53.24 20 3.41 20 3.41 1 7.54

Q 2 3 0.0099 16 51.05 20 54.02 20 3.41 20 3.41 2 7.54

I 1 4 0.0116 23 63.06 21 55.96 25 6.50 25 6.50 5 49.68

D 2 5 0.0142 21 59.65 22 58.10 24 4.18 24 4.17 12 79.43

D 1 6 0.0163 20 53.09 18 52.23 14 2.16 14 2.15 13 79.43

E 2 7 0.0187 12 41.57 10 34.37 15 2.21 15 2.21 28 318.03

V 2 8 0.0190 14 48.01 15 47.97 3 1.21 7 1.22 9 63.53

V 1 9 0.0192 10 36.28 11 36.07 3 1.21 7 1.22 8 63.53

J 2 10 0.0236 27 80.54 27 74.38 7 1.22 3 1.21 19 101.00

O 2 11 0.0254 24 78.80 26 73.15 5 1.22 5 1.21 18 101.00

O 1 12 0.0257 11 38.17 12 37.01 5 1.22 5 1.21 17 101.00

E 1 13 0.0259 1 3.71 1 2.82 11 1.95 11 1.95 14 79.72

L 2 14 0.0276 5 12.52 5 12.37 1 0.33 1 0.33 27 177.49

J 1 15 0.0287 7 26.88 7 25.61 7 1.22 3 1.21 20 101.00

L 1 16 0.0288 3 5.51 3 5.56 2 1.13 2 1.11 22 119.79

G 2 17 0.0325 22 62.98 23 59.49 18 2.81 18 2.83 25 156.12

G 1 18 0.0371 6 19.65 6 16.24 18 2.81 18 2.83 26 156.12

U 2 19 0.0461 29 90.50 30 89.07 16 2.45 16 2.41 30 540.60

U 1 20 0.0500 28 81.85 28 80.03 17 2.46 17 2.42 29 440.67

C 2 21 0.0647 4 6.62 4 6.74 12 2.13 12 2.12 4 46.49

C 1 22 0.0654 2 3.71 2 3.74 12 2.13 12 2.12 3 46.49

H 1 23 0.0998 15 49.13 16 49.75 9 1.68 9 1.67 16 86.46

H 2 24 0.1008 19 52.05 17 51.77 9 1.68 9 1.67 15 86.46

S 1 25 0.1089 25 78.95 24 71.69 22 3.97 22 3.96 24 150.35

S 2 26 0.1133 26 79.01 25 71.77 22 3.97 22 3.96 23 150.35

M 2 27 0.1634 30 90.51 29 87.21 26 6.94 28 6.73 7 57.53

F 2 28 0.1681 13 46.18 14 43.59 28 6.94 26 6.73 10 77.02

F 1 29 0.1684 8 31.92 8 30.09 28 6.94 26 6.73 11 77.02

M 1 30 0.1736 9 32.39 9 31.17 26 6.94 28 6.73 6 57.53

Table 84: Tabulation of ranked results for Class B — Left Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score threshold

that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The

Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 75. Identification and Search Enrollment

durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage

one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in Table 63. RAM is

reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 183

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0045 16 49.18 14 41.13 30 7.65 30 7.65 21 108.71

D 2 2 0.0052 20 58.67 21 57.19 24 4.15 24 4.13 12 79.43

Q 1 3 0.0057 22 62.95 23 64.04 20 3.41 20 3.41 1 7.54

Q 2 3 0.0057 21 61.29 22 61.94 20 3.41 20 3.41 2 7.54

I 1 5 0.0058 23 63.57 20 55.87 25 6.47 25 6.47 5 49.68

D 1 6 0.0072 19 53.78 19 53.32 14 2.15 14 2.14 13 79.43

E 2 7 0.0083 12 40.27 10 34.47 15 2.18 15 2.18 28 318.00

V 1 8 0.0106 10 35.66 11 35.43 3 1.19 3 1.19 8 63.53

V 2 9 0.0110 15 48.47 16 48.51 3 1.19 3 1.19 9 63.53

J 2 10 0.0126 27 77.67 27 74.09 5 1.21 5 1.20 19 101.00

O 2 11 0.0132 26 77.37 26 73.93 7 1.21 7 1.20 20 101.00

O 1 12 0.0142 11 38.08 12 35.61 7 1.21 7 1.20 17 101.00

E 1 13 0.0151 2 4.68 1 2.97 11 1.92 11 1.91 14 79.72

J 1 14 0.0156 7 25.86 7 24.14 5 1.21 5 1.20 18 101.00

L 1 15 0.0167 3 5.49 3 5.47 2 1.12 2 1.11 22 119.78

G 2 16 0.0198 13 41.12 13 37.28 18 2.76 18 2.78 25 156.12

L 2 17 0.0202 6 12.66 6 12.66 1 0.33 1 0.33 27 177.49

G 1 18 0.0212 5 11.80 5 10.13 18 2.76 18 2.78 26 156.12

U 1 19 0.0266 29 89.71 30 89.26 16 2.43 16 2.39 29 440.67

U 2 20 0.0273 28 88.88 28 80.11 17 2.43 17 2.39 30 540.59

S 1 21 0.0369 25 74.29 24 70.54 22 3.89 22 3.88 23 150.35

S 2 22 0.0381 24 73.96 25 70.84 22 3.89 22 3.88 24 150.35

C 2 23 0.0392 4 6.54 4 6.50 12 2.10 12 2.09 3 46.49

C 1 24 0.0403 1 3.70 2 3.67 12 2.10 12 2.09 4 46.49

H 1 25 0.0641 17 50.97 17 50.16 9 1.64 9 1.63 16 86.46

H 2 26 0.0647 18 52.86 18 52.84 9 1.64 9 1.63 15 86.46

M 2 27 0.1155 30 91.42 29 87.41 28 6.88 28 6.69 6 57.53

F 2 28 0.1220 14 46.58 15 45.92 26 6.86 26 6.68 10 77.02

F 1 29 0.1222 8 32.28 8 31.87 26 6.86 26 6.68 11 77.02

M 1 30 0.1259 9 33.43 9 32.03 28 6.88 28 6.69 7 57.53

Table 85: Tabulation of ranked results for Class B — Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is

an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score threshold

that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The

Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 76. Identification and Search Enrollment

durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage

one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in Table 63. RAM is

reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the

best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
184 FPVTE – FINGERPRINT MATCHING

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0015 19 57.94 17 46.13 30 15.30 30 15.33 21 108.71

Q 1 2 0.0021 20 63.99 22 65.02 20 6.84 20 6.84 2 7.54

Q 2 3 0.0022 18 53.88 19 53.40 20 6.84 20 6.84 1 7.54

I 1 3 0.0022 15 47.35 13 37.19 25 12.94 25 12.96 5 49.68

D 2 5 0.0024 24 74.21 21 63.05 24 8.31 24 8.28 13 79.43

D 1 6 0.0031 21 69.35 20 61.24 14 4.29 14 4.28 12 79.43

V 1 7 0.0036 11 39.24 15 38.93 3 2.40 7 2.40 9 63.53

V 2 7 0.0036 17 52.97 18 52.80 3 2.40 7 2.40 8 63.53

J 2 9 0.0047 26 75.92 24 69.28 7 2.42 5 2.40 17 101.00

E 2 10 0.0049 12 39.56 10 33.09 15 4.39 15 4.38 28 317.99

O 2 11 0.0051 25 74.57 23 68.46 5 2.42 3 2.40 19 101.00

L 1 12 0.0054 4 10.37 4 10.48 2 2.24 2 2.23 22 119.77

O 1 13 0.0057 13 40.42 14 38.34 5 2.42 3 2.40 20 101.00

L 2 14 0.0062 6 20.85 6 20.78 1 0.66 1 0.66 27 177.49

E 1 15 0.0063 3 8.18 2 6.12 11 3.86 11 3.85 14 79.72

J 1 16 0.0068 7 27.52 7 26.15 7 2.42 5 2.40 18 101.00

G 2 17 0.0084 14 42.86 11 34.55 18 5.59 18 5.62 25 156.12

G 1 18 0.0106 1 5.52 1 3.89 18 5.59 18 5.62 26 156.12

U 2 19 0.0124 30 91.04 28 82.40 16 4.89 17 4.83 30 540.59

U 1 20 0.0139 29 86.88 30 83.62 17 4.91 16 4.82 29 440.67

S 1 21 0.0160 28 85.05 29 83.33 22 7.82 22 7.83 23 150.35

S 2 22 0.0190 27 84.02 27 82.13 22 7.82 22 7.83 24 150.35

H 1 23 0.0349 22 70.12 25 70.38 9 3.31 9 3.31 16 86.46

H 2 24 0.0361 23 72.35 26 73.06 9 3.31 9 3.31 15 86.46

M 2 25 0.0882 16 49.50 16 45.91 28 13.79 28 13.53 6 57.53

F 2 26 0.0901 10 38.37 12 36.36 26 13.78 26 13.49 11 77.02

M 1 27 0.0904 9 28.89 8 27.15 28 13.79 28 13.53 7 57.53

F 1 28 0.0910 8 28.72 9 27.27 26 13.78 26 13.49 10 77.02

C 2 29 NA 5 10.63 5 10.70 12 4.22 12 4.20 4 46.49

C 1 30 NA 2 7.36 3 6.40 12 4.22 12 4.20 3 46.49

Table 86: Tabulation of ranked results for Class B — Left and Right Slap. Letter refers to the participant’s letter code found on the footer of this page. Sub.

# is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score threshold

that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The Identification column shows the

time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The Search Enrollment column shows the time used to create a

search template to be used for a query, as seen in Table 77. Identification and Search Enrollment durations are reported in seconds, but were originally

recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after

returning from the identification stage one initialization method, as seen in Table 63. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824

bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 185

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0009 20 60.01 16 43.86 30 19.36 30 19.36 21 108.71

Q 1 2 0.0012 14 48.85 14 42.92 20 8.89 20 8.92 1 7.54

Q 2 2 0.0012 24 71.67 24 66.01 20 8.89 20 8.92 2 7.54

I 1 2 0.0012 6 24.57 7 19.07 25 16.50 25 16.52 5 49.68

D 2 2 0.0012 19 54.37 18 46.70 24 11.90 24 11.86 13 79.43

D 1 6 0.0020 17 52.42 17 45.15 17 6.19 17 6.16 12 79.43

V 2 7 0.0024 15 49.72 19 49.30 3 3.35 7 3.36 9 63.53

E 2 7 0.0024 18 52.88 15 43.61 16 5.95 16 5.93 28 317.95

V 1 9 0.0027 10 35.51 10 34.96 3 3.35 7 3.36 8 63.53

L 1 10 0.0031 5 14.42 5 14.50 2 3.05 2 3.05 22 119.79

L 2 11 0.0033 8 28.56 9 28.59 1 0.88 1 0.88 27 177.48

J 2 11 0.0033 22 64.38 22 60.13 7 3.38 3 3.35 17 101.00

O 2 13 0.0035 21 63.87 21 60.02 5 3.38 5 3.36 20 101.00

G 2 14 0.0040 9 31.67 6 16.26 18 7.89 18 7.90 26 156.12

O 1 15 0.0041 11 37.04 11 35.64 5 3.38 5 3.36 19 101.00

E 1 16 0.0043 2 8.76 2 6.76 13 5.35 13 5.34 14 79.73

J 1 17 0.0049 7 26.31 8 25.38 7 3.38 3 3.35 18 101.00

G 1 18 0.0062 1 6.33 1 4.26 18 7.89 18 7.90 25 156.12

U 1 19 0.0099 30 88.83 28 86.60 15 5.90 15 5.82 29 440.68

S 1 20 0.0108 28 86.50 29 87.60 22 10.24 22 10.31 24 150.35

S 2 21 0.0136 29 88.70 30 88.46 22 10.24 22 10.31 23 150.35

U 2 22 0.0141 25 80.14 25 75.28 14 5.80 14 5.73 30 540.60

H 1 23 0.0203 26 82.43 26 82.66 9 4.37 9 4.37 15 86.46

H 2 24 0.0204 27 85.74 27 86.56 9 4.37 9 4.37 16 86.46

M 2 25 0.0515 23 70.45 23 65.91 26 18.36 28 18.11 6 57.53

M 1 26 0.0543 13 41.37 13 38.87 26 18.36 28 18.11 6 57.53

F 1 27 0.0591 12 39.12 12 37.56 28 18.36 26 18.07 10 77.02

F 2 27 0.0591 16 51.59 20 49.34 28 18.36 26 18.07 10 77.02

C 2 29 NA 4 10.28 4 10.21 11 5.16 11 5.13 4 46.49

C 1 30 NA 3 9.00 3 7.92 11 5.16 11 5.13 3 46.49

Table 87: Tabulation of ranked results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of this page. Sub.

# is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score threshold

that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The Identification column shows the

time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The Search Enrollment column shows the time used to create a

search template to be used for a query, as seen in Table 78. Identification and Search Enrollment durations are reported in seconds, but were originally

recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after

returning from the identification stage one initialization method, as seen in Table 63. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824

bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink.

The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
186 FPVTE – FINGERPRINT MATCHING

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 2 1 0.0010 15 56.93 10 38.28 30 17.04 30 16.99 11 110.22

Q 1 2 0.0011 10 44.75 9 36.86 20 9.14 20 9.11 2 13.33

D 2 2 0.0011 25 84.92 26 74.36 24 13.69 24 13.66 15 132.37

Q 2 4 0.0013 9 43.67 8 35.35 20 9.14 20 9.11 1 13.33

I 1 4 0.0013 23 79.70 16 52.41 29 16.71 29 16.67 4 84.42

D 1 6 0.0015 28 87.07 25 73.93 17 7.12 17 7.10 16 132.37

V 1 7 0.0024 13 47.76 14 47.02 7 3.69 7 3.66 13 121.80

V 2 7 0.0024 17 63.19 19 62.26 7 3.69 7 3.66 12 121.79

O 1 9 0.0025 21 73.31 23 68.54 4 3.63 3 3.61 19 181.00

O 2 10 0.0027 24 82.13 24 73.41 4 3.63 3 3.61 22 181.00

J 2 10 0.0027 26 85.17 28 77.75 6 3.64 6 3.62 21 181.00

J 1 12 0.0047 12 46.32 12 43.57 3 3.62 5 3.62 20 181.00

E 2 13 0.0048 27 85.50 17 52.91 12 5.21 12 5.20 28 573.25

E 1 14 0.0088 2 15.94 2 12.77 11 5.20 11 5.20 14 127.39

L 2 15 0.0095 6 21.26 6 23.53 1 3.51 1 3.48 27 274.95

L 1 16 0.0102 3 17.53 3 17.51 1 3.51 1 3.48 23 192.19

U 2 17 0.0155 20 67.98 22 68.30 15 6.13 15 5.91 29 811.45

U 1 18 0.0163 22 75.14 27 74.94 15 6.13 15 5.91 29 811.45

H 2 19 0.0275 18 64.90 20 65.36 9 5.16 9 5.16 18 144.02

G 2 20 0.0276 7 37.15 7 23.69 18 8.35 18 8.32 26 274.35

H 1 20 0.0276 19 67.91 21 68.07 9 5.16 9 5.16 17 144.02

S 1 22 0.0311 29 87.76 29 86.56 22 10.91 22 10.87 24 260.37

G 1 23 0.0368 1 11.21 1 7.71 18 8.35 18 8.32 25 274.35

C 2 24 0.0711 4 18.31 5 18.38 13 5.84 13 5.80 10 92.86

F 1 25 0.0734 14 50.99 15 51.69 27 15.96 27 15.87 7 90.93

F 2 25 0.0734 16 60.34 18 60.86 27 15.96 27 15.87 6 90.93

M 2 27 0.0826 11 45.96 13 46.70 25 15.91 25 15.83 8 90.93

M 1 28 0.0934 8 42.60 11 43.37 25 15.91 25 15.83 5 90.93

S 2 29 0.1680 30 89.24 30 91.74 22 10.91 22 10.87 3 61.04

C 1 30 NA 5 21.04 4 18.30 13 5.84 13 5.80 9 92.86

Table 88: Tabulation of ranked results for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the score

threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed. The Identification column

shows the time used to perform a search over an enrollment set of 5 000 000, as seen in Table 20. The Search Enrollment column shows the time used

to create a search template to be used for a query, as seen in Table 79. Identification and Search Enrollment durations are reported in seconds, but were

originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute

nodes after returning from the identification stage one initialization method, as seen in Table 64. RAM is reported in gigabytes, where 1 GB is equal to

1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the

worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 187

Participant

FNIR

Identification Search Enrollment RAM

Letter Sub. # Mean Median Mean Median

I 1 1 0.0013 24 79.04 15 54.56 25 20.21 25 20.23 4 113.80

Q 2 2 0.0014 27 83.35 25 74.22 17 12.95 17 13.06 2 20.22

I 2 2 0.0014 9 40.53 7 30.82 24 18.72 24 18.73 11 137.03

D 1 4 0.0015 17 65.97 17 58.92 23 17.44 21 17.39 10 132.40

Q 1 5 0.0017 26 83.25 26 74.40 17 12.95 17 13.06 1 20.22

V 1 5 0.0017 10 40.94 10 40.74 9 8.48 9 8.50 17 234.03

D 2 7 0.0018 30 86.39 27 74.97 30 30.43 30 30.47 9 132.37

V 2 8 0.0019 16 65.47 18 65.07 9 8.48 9 8.50 18 234.03

O 2 9 0.0033 19 72.55 21 69.30 6 6.80 6 6.71 23 303.13

J 2 9 0.0033 20 72.62 19 67.98 8 6.82 8 6.74 24 303.13

O 1 11 0.0034 15 59.01 14 54.42 6 6.80 6 6.71 25 303.13

E 2 12 0.0050 14 57.02 11 42.73 11 9.89 11 9.91 30 930.48

J 1 13 0.0051 8 36.09 9 33.02 5 6.78 5 6.69 22 303.13

L 2 14 0.0083 3 19.52 5 20.25 3 4.36 3 4.36 26 367.82

C 2 15 0.0085 5 25.91 6 21.97 13 10.79 13 10.69 15 183.36

C 1 16 0.0094 4 25.25 4 20.15 13 10.79 13 10.69 14 183.36

L 1 17 0.0097 7 31.42 8 31.68 3 4.36 3 4.36 21 280.49

E 1 18 0.0106 1 9.52 2 8.63 12 9.90 12 9.92 16 191.66

H 2 19 0.0199 29 84.26 29 84.50 15 12.08 15 12.17 12 144.02

H 1 20 0.0201 28 84.14 30 84.51 15 12.08 15 12.17 13 144.02

G 2 21 0.0333 6 30.61 3 19.46 19 15.55 19 15.50 19 261.29

U 2 22 0.0351 23 74.39 24 72.48 1 2.94 1 2.87 28 806.17

U 1 23 0.0358 25 82.76 28 82.61 1 2.94 1 2.87 28 806.17

G 1 24 0.0447 2 11.67 1 7.78 19 15.55 19 15.50 20 261.29

F 1 25 0.0536 13 55.63 16 55.79 28 21.07 28 20.92 7 130.29

F 2 25 0.0536 18 68.61 20 68.20 28 21.07 28 20.92 6 130.29

M 2 27 0.0716 12 48.71 13 48.80 26 21.02 26 20.89 5 130.29

M 1 28 0.0783 11 47.38 12 48.08 26 21.02 26 20.89 8 130.29

S 1 29 0.0860 22 74.01 22 69.71 21 17.43 22 17.57 27 382.88

S 2 30 0.2462 21 72.95 23 70.77 21 17.43 22 17.57 3 78.28

Table 89: Tabulation of ranked results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on the footer of this

page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. The FNIR column was computed at the

score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set of 5 000 000, as seen

in Table 20. The Search Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 80. Identification and

Search Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set

sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method, as seen in

Table 65. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise

ranking, with the best performance shaded in green and the worst in pink. The table is sorted on the FNIR column-wise ranking.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
188 FPVTE – FINGERPRINT MATCHING

J Relative Combined Results

The tables in Appendix I show the detailed values for FNIR at a fixed FPIR of 10−3, identification time, search template

enrollment time, and RAM consumption. While the column-wise ranking for each variable is given, it can be difficult to visualize relative comparisons among submissions for each of these values. Use of star plots can help with this visualization.

For more information on how to read star plots, please refer to the explanation in Appendix K.

Class A plots are in Figures 99 through 101, Class B plots are in Figures 102 through 105, and Class C plots are in Figures 106

through 107.

Some notable observations based on the plotted shape include that:

. For almost all finger combinations, I uses the longest enrollment times while providing the highest accuracy.

. D’s submission strike a balance between identification time and enrollment time in order to provide high accuracy.

. Class A results are nearly identical, regardless of which index finger combinations are used.

. J1, L1, Q, O1, and V1 provide high accuracy while limiting time and computational resources for most finger combinations.

. Shapes formed by participants appear to remain similar regardless of finger combination.

. Tradeoffs between a participant’s two submissions are very easily seen. For instance, in class Class A, V1 and S1 use

significantly shorter identification times than V2 and S2 respectively, but result in similar relative accuracies.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 189

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 K1 K2

L1 L2 M1 M2 O1 O2

P1 P2 Q1 Q2 S1 S2

T1 T2 U1 U2 V1 V2

Figure 99: Star plot of combined results for Class A — Left Index. The values in this plot have been independently scaled from 0 to 1 from the values

printed in Table 81, with the exception of FNIR, whose log10 values were scaled. Any values printed as NA were set to 1 before scaling. The intersection

point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above

each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two submissions

each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
190 FPVTE – FINGERPRINT MATCHING RAM Consumption

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F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 K1 K2

L1 L2 M1 M2 O1 O2

P1 P2 Q1 Q2 S1 S2

T1 T2 U1 U2 V1 V2

Figure 100: Star plot of combined results for Class A — Right Index. The values in this plot have been independently scaled from 0 to 1 from the values

printed in Table 82, with the exception of FNIR, whose log10 values were scaled. The intersection point of a radius and the circumference of a circle

indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above each plot represents the participant’s letter code

found on the footer of this page and an identifier used to differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 191

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I1 I2 J1 J2 K1 K2

L1 L2 M1 M2 O1 O2

P1 P2 Q1 Q2 S1 S2

T1 T2 U1 U2 V1 V2

Figure 101: Star plot of combined results for Class A — Left and Right Index. The values in this plot have been independently scaled from 0 to 1 from

the values printed in Table 21, with the exception of FNIR, whose log10 values were scaled. Any values printed as NA were set to 1 before scaling. The

intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle.

The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two

submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
192 FPVTE – FINGERPRINT MATCHING

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S1 S2 U1 U2 V1 V2

Figure 102: Star plot of combined results for Class B — Left Slap. The values in this plot have been independently scaled from 0 to 1 from the values

printed in Table 84, with the exception of FNIR, whose log10 values were scaled. The intersection point of a radius and the circumference of a circle

indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above each plot represents the participant’s letter code

found on the footer of this page and an identifier used to differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 193

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 103: Star plot of combined results for Class B — Right Slap. The values in this plot have been independently scaled from 0 to 1 from the values

printed in Table 85, with the exception of FNIR, whose log10 values were scaled. The intersection point of a radius and the circumference of a circle

indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above each plot represents the participant’s letter code

found on the footer of this page and an identifier used to differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
194 FPVTE – FINGERPRINT MATCHING

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 104: Star plot of combined results for Class B — Left and Right Slap. The values in this plot have been independently scaled from 0 to 1 from

the values printed in Table 86, with the exception of FNIR, whose log10 values were scaled. Any values printed as NA were set to 1 before scaling. The

intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle.

The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two

submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 195

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 105: Star plot of combined results for Class B — Identification Flats. The values in this plot have been independently scaled from 0 to 1 from the

values printed in Table 22, with the exception of FNIR, whose log10 values were scaled. Any values printed as NA were set to 1 before scaling. The

intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle.

The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two

submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
196 FPVTE – FINGERPRINT MATCHING

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F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 106: Star plot of combined results for Class C — Ten-Finger Plain-to-Plain. The values in this plot have been independently scaled from 0 to 1

from the values printed in Table 88, with the exception of FNIR, whose log10 values were scaled. Any values printed as NA were set to 1 before scaling.

The intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle.

The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two

submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 197

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S1 S2 U1 U2 V1 V2

Figure 107: Star plot of combined results for Class C — Ten-Finger Rolled-to-Rolled. The values in this plot have been independently scaled from 0 to 1

from the values printed in Table 23, with the exception of FNIR, whose log10 values were scaled. The intersection point of a radius and the circumference

of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above each plot represents the participant’s

letter code found on the footer of this page and an identifier used to differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
198 FPVTE – FINGERPRINT MATCHING

K Relative Accuracy and Number of Fingers

In Section 7, DETs, tables, and other data visualization methods were used to show exact FNIR values at FPIR = 10−3.

While this data is important for exact comparisons, it is difficult to quickly compare relative accuracy among submissions,

or to see how a submission fares across finger combinations. To facilitate these comparisons, star plots [1] (also called

spider or radar plots) are included in this section. These plots are used to quickly examine relative values among multiple

variables.

In each star plot, values are plotted along multiple radii, where each radius represents a single variable. The plot area is

delineated with three circles. The points on the circumference of these circles indicate different values where they intersect

the radii. The intersection with the smallest circle represents 0, the next-largest circle (dashed-blue) represents 0.5, and the

largest circle (dashed-gray) represents 1. All values plotted have been scaled between 0 and 1 against other values for the

same variable in order to fit within the largest circle. These plotted values were then connected to adjacent plotted values,

creating a polygon. Many traits may be quickly inferred by the shape of these polygons:

. Regular polygons indicate submissions that have similar accuracy for all plotted variables.

. A submission that is the most accurate in terms of every variable would inscribe the center circle and the least

accurate would inscribe the largest circle.

. The smaller the polygon, the more accurate the submission.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 199

K.1 Class A

Relative FNIR results for left index, right index, and left and right index searches are shown in Figure 108. Note that the

enrollment set sizes differed between single index and two-index searches.

Some notable observations include:

. The most accurate submissions (D, I, Q, V) are instantly recognizable by their small shape.

. Most submissions have near-identical accuracy, regardless of being provided one or two index fingers, as indicated

by the equilateral triangle drawn. This may have impacts on data collection and storage. Extreme examples include

D, K, M, and V.

. No participants appear to have wildly-differing accuracy among any of the index finger combinations.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
200 FPVTE – FINGERPRINT MATCHING Left and Right Index

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C1 C2 D1 D2 E1 E2

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I1 I2 J1 J2 K1 K2

L1 L2 M1 M2 O1 O2

P1 P2 Q1 Q2 S1 S2

T1 T2 U1 U2 V1 V2

Figure 108: Star plots of relative accuracy for Class A. Values plotted along each radius are log10 of values from Tables 7 through 9, scaled independently

from 0 to 1. Values printed as NA in those tables were set to 1 prior to scaling. 30 000 searches were run against an enrollment set of 100 000 subjects for

left index and right index, and 1 600 000 subjects for left and right index. The intersection point of a radius and the circumference of a circle indicate the

scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle. The title above each plot represents the participant’s letter code found on the

footer of this page and an identifier used to differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 201

K.2 Class B

Relative FNIR results for left slap, right slap, left and right slap, and IDFlat searches are shown in Figure 109. Some notable

observations include:

. The most accurate submissions (I and Q) are instantly recognizable by their small shape.

. The most accurate submissions are also square, meaning they perform equally well for all finger combinations.

. Most submissions appear to skew towards slightly worse accuracy on left slap and right slap searches, as indicated

by the obtuse angles at the vertices for IDFlats and left and right slap.

. Some submissions, like C, F, H, M, and S, vary significantly as the number of fingers at their disposal changes.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
202 FPVTE – FINGERPRINT MATCHING

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 109: Star plots of relative accuracy for Class B. Values plotted along each radius are log10 of values from Tables 10 through 13, scaled independently

from 0 to 1. Values printed as NA in those tables were set to 1 prior to scaling. 30 000 searches were run against an enrollment set of 3 000 000 subjects.

The intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashed-gray circle.

The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate between the two

submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 203

K.3 Class C

Relative FNIR results for ten-finger plain-to-plain, ten-finger rolled-to-rolled, and ten-finger plain-to-rolled searches are

shown in Figure 110. Some notable observations include:

. The most accurate submissions (D, I, and Q) are instantly recognizable by their small shape and are seemingly

equilateral, indicating that they perform equally well for all finger combinations.

. Many submissions had lower accuracy with plain-to-rolled searching over searching homogeneous impressions,

including F, G, and M.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
204 FPVTE – FINGERPRINT MATCHING

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 110: Star plots of relative accuracy for Class C. Values plotted along each radius are log10 of values from Tables 14 through 16, scaled independently from 0 to 1. Values printed as NA in those tables were set to 1 prior to scaling. 30 000 searches were run against an enrollment set of 5 000 000

subjects. The intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on the outer dashedgray circle. The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to differentiate

between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 205

K.4 All Classes

Relative FNIR results for left and right index, IDFlat, and ten-finger rolled-to-rolled searches are shown in Figure 111.

Note that the enrollment set sizes differed between all three finger searching combinations. Some notable observations

include:

. The top-performing submissions from Class A, B, and C (D, I, Q, and V) are instantly recognizable by their small

shape.

. Many of the most accurate submissions from all three classes appear equally as accurate in each individual class.

. If a submission had trouble with a particular class in FpVTE, it appears to be Class C, as seen by the long line

segments extending from the ten-finger rolled-to-rolled vertex in most plots that do not contain a mostly equilateral

triangle.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
206 FPVTE – FINGERPRINT MATCHING

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C1 C2 D1 D2 E1 E2

F1 F2 G1 G2 H1 H2

I1 I2 J1 J2 L1 L2

M1 M2 O1 O2 Q1 Q2

S1 S2 U1 U2 V1 V2

Figure 111: Star plots of relative accuracy for two-index finger, IDFlat, and ten-finger rolled-to-rolled comparisons. Values plotted along each radius

are log10 of values from Tables 9, 13, and 15, scaled independently from 0 to 1. Values printed as NA in those tables were set to 1 prior to scaling.

30 000 searches were run against an enrollment set of 1 600 000 subjects for left and right index, 3 000 000 subjects for IDFlats, and 5 000 000 subjects for

ten-finger rolled-to-rolled. The intersection point of a radius and the circumference of a circle indicate the scaled values 0, 0.5, and 1, with 1 resting on

the outer dashed-gray circle. The title above each plot represents the participant’s letter code found on the footer of this page and an identifier used to

differentiate between the two submissions each participant could make.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 207

L Combined Sorted Rankings for a Theoretical Use Case

In prior sections, numerous tables and plots were presented showcasing individual statistics of participant submissions.

Tables 91 through 98 attempt to coalesce all the presented identification statistics and categorize the overall performance

of the submissions. Note that these rankings are theoretical and do not imply quality or endorsement of any kind. Please

read the disclaimer for more information.

For each statistic, the values and overall ranks from Sections 7 through 9 are displayed. The Score column is computed

by weighting percentiles of the results per class. The weights and percentiles were chosen based on values that provided

reasonable and consistent results across all enrollment sets for all classes.

. Search Template Enrollment Time

+2B ⇐⇒ Vf ≤ P10 or

+b ⇐⇒ Vf ≤ P15 or

−b ⇐⇒ Vf ≥ P85

. FNIR

+(N − RFNIR)

+5B ⇐⇒ Vf ≤ P5 or

+3B ⇐⇒ Vf ≤ P15 or

+B ⇐⇒ Vf ≤ P5 or

−5B ⇐⇒ Vf ≥ P95 or

−3B ⇐⇒ Vf ≥ P90 or

−B ⇐⇒ Vf ≥ P75

. RAM Consumption

+2b ⇐⇒ Vf ≤ P10 or

+b ⇐⇒ Vf ≤ P15 or

−2B ⇐⇒ Vf ≥ P85

. Identification Time

+(N − RTime)

+2B ⇐⇒ Vf ≤ P10 or

+B ⇐⇒ Vf ≤ P15 or

−2B ⇐⇒ Vf ≥ P90 or

−B ⇐⇒ Vf ≥ P85

where N = number of participants for finger

B = max (N/2.0, 15)

b = max (N/6.0, 3)

Rf = submission’s rank for factor f

Vf = submission’s value for factor f

Px = x

thpercentile of Vf

As shown, the primary factors used in scoring were accuracy and identification speed. While enrollment speed is important, the FpVTE API limited the time that could be used, and most participants completed enrollment in a relatively

similar timeframe. Using a very high amount of RAM was penalized heavily, as greater amounts of RAM require additional compute nodes, while less RAM could allow additional identification processes to be run, decreasing search time.

High accuracy was rewarded the most of any factor—regardless of how fast or resource-friendly a submission is, it doesn’t

matter if the results are incorrect.

The color bands are indicative of the 80th percentile, 55th percentile, and below. The best performance in each category is

shaded in green and the worst in pink. Time values in the Identification and Enroll columns are reported in seconds, but

were originally recorded to microsecond precision. RAM is the sum of the resident set sizes of the stage one identification

processes over all compute nodes after returning from the identification stage one initialization method.

Some notable observations from Tables 90 through 98 include:

. Some of the most accurate submissions used such a small amount of RAM that only a single compute node was

necessary.

. The most accurate submissions did not use the entire 90 seconds to perform identifications. This dramatically reduced the score given to submissions that used the maximum amount of time but were not with the top accuracy

range.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
208 FPVTE – FINGERPRINT MATCHING

. In Class C, there are a number of submissions that achieve an “acceptable” level of accuracy in much less time than

the most accurate submissions.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 209

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

< 20 seconds

D 1 109 1 0.0197 20 7.32 29 1.43 19 0.61

L 1 95 8 0.0625 2 0.29 1 0.05 26 1.14

V 1 82 4 0.0253 19 6.01 10 0.32 17 0.39

Q 2 79 3 0.0226 24 10.43 19 0.54 14 0.34

Q 1 74 2 0.0222 28 15.70 19 0.54 13 0.34

I 1 73 5 0.0257 22 9.94 30 1.46 20 0.70

J 1 73 14 0.0786 4 0.54 11 0.32 9 0.32

O 1 60 15 0.0818 5 0.62 4 0.27 15 0.35

E 1 59 12 0.0745 3 0.35 13 0.35 25 1.12

L 2 57 6 0.0351 12 3.32 3 0.15 28 2.32

C 1 50 24 0.1335 1 0.26 17 0.39 7 0.18

O 2 43 13 0.0766 9 1.56 4 0.27 15 0.35

T 2 43 9 0.0685 18 5.97 8 0.31 1 0.01

J 2 43 10 0.0712 7 1.25 11 0.32 9 0.32

F 2 27 18 0.1082 14 3.56 25 1.07 5 0.18

P 2 25 22 0.1272 13 3.33 15 0.36 22 0.78

F 1 24 20 0.1111 11 2.49 25 1.07 6 0.18

G 1 20 19 0.1089 21 9.74 21 0.55 18 0.57

C 2 14 25 0.1337 6 0.76 17 0.39 8 0.18

P 1 14 23 0.1308 8 1.32 15 0.36 23 0.78

S 1 10 7 0.0571 29 16.86 22 0.88 21 0.72

H 1 5 26 0.1576 15 3.61 6 0.30 11 0.33

H 2 1 27 0.1607 17 4.13 6 0.30 11 0.33

U 1 −2 21 0.1218 27 14.42 2 0.15 27 1.70

K 2 −10 16 0.0875 23 10.32 23 1.05 30 3.87

E 2 −11 11 0.0723 30 16.90 13 0.35 24 1.11

K 1 −12 17 0.0883 25 10.44 23 1.05 29 3.87

M 1 −49 29 0.2995 10 1.84 27 1.07 3 0.14

T 1 −51 30 NA 16 3.99 8 0.31 2 0.01

M 2 −55 28 0.2921 26 10.70 27 1.07 4 0.14

≥ 20 seconds

D 2 84 1 0.0197 3 41.84 5 1.42 3 0.61

S 2 4 4 0.0650 4 44.66 4 0.88 4 0.72

I 2 3 3 0.0278 2 40.99 6 2.15 5 1.04

V 2 −5 2 0.0252 6 65.35 2 0.32 1 0.39

G 2 −13 5 0.1086 5 54.03 3 0.55 2 0.57

U 2 −40 6 0.1178 1 24.16 1 0.15 6 1.42

Table 90: Tabulation of operationally-ranked results for Class A — Left Index. Submissions were split into two groups. The first group includes

submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer.

Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each

participant could make. Score refers to the sum of the scoring equations shown in Appendix L. The color bands are indicative of the 80th percentile,

55th percentile, and below of the Score column. The FNIR column was computed at the score threshold that gave FPIR = 10−3. NA indicates that the

operations required to produce the value could not be performed. The Identification column shows the time used to perform a search over an enrollment

set of 100 000, as seen in Table 17. The Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 72.

Identification and Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the

resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method,

as seen in Table 60. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s

column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
210 FPVTE – FINGERPRINT MATCHING

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

< 20 seconds

Q 2 111 2 0.0214 23 9.98 19 0.54 11 0.33

D 1 109 1 0.0190 20 7.46 29 1.43 19 0.61

L 1 95 8 0.0505 2 0.26 1 0.05 26 1.14

V 1 81 5 0.0223 18 5.60 10 0.32 17 0.39

E 1 76 11 0.0630 3 0.32 13 0.36 24 1.07

I 1 74 3 0.0215 22 9.83 30 1.46 20 0.69

O 1 58 17 0.0776 5 0.56 4 0.27 15 0.34

L 2 57 6 0.0295 13 3.26 3 0.16 28 2.32

J 1 55 16 0.0708 4 0.51 11 0.33 10 0.31

C 1 50 24 0.1132 1 0.24 17 0.39 7 0.17

Q 1 43 4 0.0218 28 14.24 19 0.54 11 0.33

O 2 43 13 0.0675 9 1.36 4 0.27 16 0.34

T 2 43 9 0.0562 19 5.87 8 0.31 1 0.01

J 2 41 12 0.0643 7 1.13 11 0.33 9 0.31

F 2 27 18 0.0903 15 3.60 25 1.09 5 0.17

P 2 25 22 0.1100 12 3.07 15 0.37 23 0.76

F 1 24 20 0.0933 11 2.38 25 1.09 6 0.17

G 1 20 19 0.0910 24 10.10 21 0.55 18 0.57

C 2 16 23 0.1124 6 0.69 17 0.39 8 0.18

P 1 12 25 0.1133 8 1.24 15 0.37 22 0.76

S 1 9 7 0.0442 30 16.55 22 0.88 21 0.71

H 1 5 26 0.1230 14 3.56 6 0.30 14 0.33

H 2 1 27 0.1249 17 4.05 6 0.30 13 0.33

U 1 −3 21 0.0996 27 10.76 2 0.15 27 1.56

K 2 −9 15 0.0685 25 10.27 23 1.05 29 3.87

K 1 −9 14 0.0682 26 10.42 23 1.05 30 3.87

E 2 −10 10 0.0624 29 16.27 13 0.36 25 1.07

T 1 −19 28 0.1929 16 3.73 8 0.31 1 0.01

M 1 −50 30 0.2615 10 1.78 27 1.09 3 0.14

M 2 −80 29 0.2526 21 9.39 27 1.09 3 0.14

≥ 20 seconds

D 2 84 1 0.0190 2 28.64 5 1.43 3 0.61

I 2 19 2 0.0214 3 40.35 6 2.15 5 1.01

S 2 4 4 0.0503 4 46.05 4 0.88 4 0.71

G 2 −13 5 0.0909 5 59.55 3 0.55 2 0.57

V 2 −21 3 0.0222 6 61.24 2 0.32 1 0.39

U 2 −40 6 0.1007 1 20.10 1 0.15 6 1.30

Table 91: Tabulation of operationally-ranked results for Class A — Right Index. Submissions were split into two groups. The first group includes

submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds or longer.

Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each

participant could make. Score refers to the sum of the scoring equations shown in Appendix L. The color bands are indicative of the 80th percentile,

55th percentile, and below of the Score column. The FNIR column was computed at the score threshold that gave FPIR = 10−3. The Identification column

shows the time used to perform a search over an enrollment set of 100 000, as seen in Table 17. The Enrollment column shows the time used to create a

search template to be used for a query, as seen in Table 73. Identification and Enrollment durations are reported in seconds, but were originally recorded

to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all compute nodes after returning

from the identification stage one initialization method, as seen in Table 61. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The

number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. The table is

sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 211

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

< 20 seconds

V 1 87 1 0.0034 5 9.29 3 0.64 5 11.77

L 1 43 4 0.0146 2 2.19 1 0.11 8 18.76

J 1 24 3 0.0143 6 13.64 4 0.65 3 8.30

I 1 19 2 0.0058 8 17.87 9 2.93 6 15.83

C 1 12 7 0.0368 1 2.08 5 0.78 2 4.87

O 1 9 5 0.0229 7 14.46 2 0.53 4 9.05

C 2 −3 8 0.0374 4 6.35 5 0.78 1 4.87

K 1 −44 6 0.0360 9 18.01 8 2.09 9 61.81

G 1 −69 9 0.0515 3 5.22 7 1.09 7 16.38

≥ 20 seconds

Q 2 109 1 0.0027 19 161.02 15 1.08 9 9.14

Q 1 107 1 0.0027 21 212.69 15 1.08 10 9.14

L 2 89 7 0.0072 3 23.42 3 0.31 26 53.98

V 2 78 3 0.0028 18 127.65 9 0.64 13 11.77

D 1 74 4 0.0030 15 70.99 25 2.84 17 18.58

E 1 71 11 0.0207 1 16.35 11 0.70 22 33.40

S 1 70 13 0.0281 2 23.00 18 1.75 14 14.82

D 2 68 4 0.0030 23 237.43 26 2.84 17 18.58

J 2 39 8 0.0143 7 33.35 10 0.65 7 8.30

O 2 36 12 0.0214 10 43.53 4 0.53 8 9.05

I 2 36 4 0.0030 25 338.88 27 4.30 21 30.83

T 2 35 19 0.0366 9 37.23 7 0.62 1 0.01

U 1 26 17 0.0336 11 45.51 1 0.30 25 44.63

P 2 21 16 0.0333 17 101.16 13 0.72 19 21.41

P 1 20 20 0.0370 14 63.65 13 0.72 20 21.42

G 2 17 15 0.0311 22 221.16 17 1.09 16 16.38

H 1 7 24 0.0686 8 36.71 5 0.60 12 9.36

F 1 5 21 0.0386 13 60.66 21 2.15 5 4.86

K 2 4 14 0.0286 6 32.93 20 2.09 27 61.81

H 2 4 23 0.0684 12 52.25 5 0.60 11 9.36

F 2 2 22 0.0412 16 73.95 21 2.15 5 4.86

U 2 −3 18 0.0358 24 240.40 1 0.30 24 37.35

S 2 −11 9 0.0195 26 495.50 18 1.75 14 14.82

E 2 −13 10 0.0202 27 518.11 11 0.70 23 33.41

T 1 −28 27 NA 4 25.68 7 0.62 1 0.01

M 2 −36 25 NA 20 171.24 23 2.16 4 3.76

M 1 −48 26 NA 5 31.44 23 2.16 3 3.75

Table 92: Tabulation of operationally-ranked results for Class A — Left and Right Index. Submissions were split into two groups. The first group

includes submissions that performed searches on average in less than 20 seconds, and the second includes those that took, on average, 20 seconds

or longer. Letter refers to the participant’s letter code found on the footer of this page. Sub. # is an identifier used to differentiate between the two

submissions each participant could make. Score refers to the sum of the scoring equations shown in Appendix L. The color bands are indicative of the

80th percentile, 55th percentile, and below of the Score column. The FNIR column was computed at the score threshold that gave FPIR = 10−3. NA

indicates that the operations required to produce the value could not be performed. The Identification column shows the time used to perform a search

over an enrollment set of 1 600 000, as seen in Table 18. The Enrollment column shows the time used to create a search template to be used for a query,

as seen in Table 74. Identification and Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers

to the sum of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one

initialization method, as seen in Table 62. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value

provides the value’s column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
212 FPVTE – FINGERPRINT MATCHING

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

Q 1 126 2 0.0098 19 53.24 20 3.41 1 7.54

I 2 111 1 0.0094 13 38.26 30 7.67 21 108.71

L 1 101 16 0.0288 3 5.56 2 1.11 22 119.79

Q 2 96 3 0.0099 20 54.02 20 3.41 2 7.54

I 1 83 4 0.0116 21 55.96 25 6.50 5 49.68

V 2 83 8 0.0190 15 47.97 7 1.22 9 63.53

D 2 79 5 0.0142 22 58.10 24 4.17 12 79.43

C 1 76 22 0.0654 2 3.74 12 2.12 3 46.49

E 1 76 13 0.0259 1 2.82 11 1.95 14 79.72

V 1 71 9 0.0192 11 36.07 7 1.22 8 63.53

L 2 56 14 0.0276 5 12.37 1 0.33 27 177.49

C 2 55 21 0.0647 4 6.74 12 2.12 4 46.49

D 1 49 6 0.0163 18 52.23 14 2.15 13 79.43

O 1 42 12 0.0257 12 37.01 5 1.21 17 101.00

J 1 38 15 0.0287 7 25.61 3 1.21 20 101.00

O 2 30 11 0.0254 26 73.15 5 1.21 18 101.00

E 2 26 7 0.0187 10 34.37 15 2.21 28 318.03

G 2 21 17 0.0325 23 59.49 18 2.83 25 156.12

J 2 8 10 0.0236 27 74.38 3 1.21 19 101.00

H 1 7 23 0.0998 16 49.75 9 1.67 16 86.46

G 1 6 18 0.0371 6 16.24 18 2.83 26 156.12

H 2 2 24 0.1008 17 51.77 9 1.67 15 86.46

S 1 −5 25 0.1089 24 71.69 22 3.96 24 150.35

S 2 −22 26 0.1133 25 71.77 22 3.96 23 150.35

F 2 −31 28 0.1681 14 43.59 26 6.73 10 77.02

M 2 −47 27 0.1634 29 87.21 28 6.73 7 57.53

U 1 −48 20 0.0500 28 80.03 17 2.42 29 440.67

U 2 −48 19 0.0461 30 89.07 16 2.41 30 540.60

F 1 −57 29 0.1684 8 30.09 26 6.73 11 77.02

M 1 −59 30 0.1736 9 31.17 28 6.73 6 57.53

Table 93: Tabulation of operationally-ranked results for Class B — Left Slap. Letter refers to the participant’s letter code found on the footer of this page.

Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of the scoring equations

shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The FNIR column was

computed at the score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set

of 3 000 000, as seen in Table 19. The Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 75.

Identification and Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the

resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method,

as seen in Table 63. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s

column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 213

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

I 2 113 1 0.0045 14 41.13 30 7.65 21 108.71

D 2 113 2 0.0052 21 57.19 24 4.13 12 79.43

L 1 102 15 0.0167 3 5.47 2 1.11 22 119.78

Q 2 91 3 0.0057 22 61.94 20 3.41 2 7.54

Q 1 90 3 0.0057 23 64.04 20 3.41 1 7.54

V 1 87 8 0.0106 11 35.43 3 1.19 8 63.53

I 1 82 5 0.0058 20 55.87 25 6.47 5 49.68

E 1 75 13 0.0151 1 2.97 11 1.91 14 79.72

V 2 66 9 0.0110 16 48.51 3 1.19 9 63.53

C 1 55 24 0.0403 2 3.67 12 2.09 4 46.49

D 1 50 6 0.0072 19 53.32 14 2.14 13 79.43

J 1 44 14 0.0156 7 24.14 5 1.20 18 101.00

C 2 43 23 0.0392 4 6.50 12 2.09 3 46.49

O 1 37 12 0.0142 12 35.61 7 1.20 17 101.00

L 2 37 17 0.0202 6 12.66 1 0.33 27 177.49

G 2 31 16 0.0198 13 37.28 18 2.78 25 156.12

E 2 26 7 0.0083 10 34.47 15 2.18 28 318.00

G 1 22 18 0.0212 5 10.13 18 2.78 26 156.12

S 2 14 22 0.0381 25 70.84 22 3.88 24 150.35

S 1 14 21 0.0369 24 70.54 22 3.88 23 150.35

J 2 13 10 0.0126 27 74.09 5 1.20 19 101.00

O 2 8 11 0.0132 26 73.93 7 1.20 20 101.00

H 1 3 25 0.0641 17 50.16 9 1.63 16 86.46

H 2 1 26 0.0647 18 52.84 9 1.63 15 86.46

F 2 −32 28 0.1220 15 45.92 26 6.68 10 77.02

M 2 −47 27 0.1155 29 87.41 28 6.69 6 57.53

U 1 −48 19 0.0266 30 89.26 16 2.39 29 440.67

U 2 −48 20 0.0273 28 80.11 17 2.39 30 540.59

F 1 −57 29 0.1222 8 31.87 26 6.68 11 77.02

M 1 −59 30 0.1259 9 32.03 28 6.69 7 57.53

Table 94: Tabulation of operationally-ranked results for Class B — Right Slap. Letter refers to the participant’s letter code found on the footer of this page.

Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of the scoring equations

shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The FNIR column was

computed at the score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an enrollment set

of 3 000 000, as seen in Table 19. The Enrollment column shows the time used to create a search template to be used for a query, as seen in Table 76.

Identification and Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the

resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization method,

as seen in Table 63. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s

column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
214 FPVTE – FINGERPRINT MATCHING

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

Q 1 123 2 0.0021 22 65.02 20 6.84 2 7.54

I 2 110 1 0.0015 17 46.13 30 15.33 21 108.71

Q 2 94 3 0.0022 19 53.40 20 6.84 1 7.54

I 1 92 3 0.0022 13 37.19 25 12.96 5 49.68

L 1 89 12 0.0054 4 10.48 2 2.23 22 119.77

V 1 87 7 0.0036 15 38.93 7 2.40 9 63.53

V 2 81 7 0.0036 18 52.80 7 2.40 8 63.53

D 2 76 5 0.0024 21 63.05 24 8.28 13 79.43

E 1 72 15 0.0063 2 6.12 11 3.85 14 79.72

D 1 48 6 0.0031 20 61.24 14 4.28 12 79.43

G 1 41 18 0.0106 1 3.89 18 5.62 26 156.12

L 2 40 14 0.0062 6 20.78 1 0.66 27 177.49

O 1 39 13 0.0057 14 38.34 3 2.40 20 101.00

J 1 37 16 0.0068 7 26.15 5 2.40 18 101.00

O 2 29 11 0.0051 23 68.46 3 2.40 19 101.00

G 2 29 17 0.0084 11 34.55 18 5.62 25 156.12

J 2 10 9 0.0047 24 69.28 5 2.40 17 101.00

E 2 8 10 0.0049 10 33.09 15 4.38 28 317.99

M 1 4 27 0.0904 8 27.15 28 13.53 7 57.53

F 2 4 26 0.0901 12 36.36 26 13.49 11 77.02

H 1 0 23 0.0349 25 70.38 9 3.31 16 86.46

M 2 −1 25 0.0882 16 45.91 28 13.53 6 57.53

H 2 −2 24 0.0361 26 73.06 9 3.31 15 86.46

S 2 −4 22 0.0190 27 82.13 22 7.83 24 150.35

C 1 −7 30 NA 3 6.40 12 4.20 3 46.49

S 1 −19 21 0.0160 29 83.33 22 7.83 23 150.35

F 1 −26 28 0.0910 9 27.27 26 13.49 10 77.02

C 2 −29 29 NA 5 10.70 12 4.20 4 46.49

U 1 −49 20 0.0139 30 83.62 16 4.82 29 440.67

U 2 −49 19 0.0124 28 82.40 17 4.83 30 540.59

Table 95: Tabulation of operationally-ranked results for Class B — Left and Right Slap. Letter refers to the participant’s letter code found on the footer

of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of the scoring

equations shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The FNIR column

was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed.

The Identification column shows the time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The Enrollment column shows

the time used to create a search template to be used for a query, as seen in Table 77. Identification and Enrollment durations are reported in seconds,

but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all

compute nodes after returning from the identification stage one initialization method, as seen in Table 63. RAM is reported in gigabytes, where 1 GB is

equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green

and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 215

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

I 1 132 2 0.0012 7 19.07 25 16.52 5 49.68

Q 1 129 2 0.0012 14 42.92 20 8.92 1 7.54

Q 2 119 2 0.0012 24 66.01 20 8.92 2 7.54

D 2 114 2 0.0012 18 46.70 24 11.86 13 79.43

I 2 109 1 0.0009 16 43.86 30 19.36 21 108.71

L 1 90 10 0.0031 5 14.50 2 3.05 22 119.79

V 2 83 7 0.0024 19 49.30 7 3.36 9 63.53

E 1 72 16 0.0043 2 6.76 13 5.34 14 79.73

G 1 71 18 0.0062 1 4.26 18 7.90 25 156.12

V 1 71 9 0.0027 10 34.96 7 3.36 8 63.53

D 1 52 6 0.0020 17 45.15 17 6.16 12 79.43

L 2 41 11 0.0033 9 28.59 1 0.88 27 177.48

O 1 39 15 0.0041 11 35.64 5 3.36 19 101.00

J 1 36 17 0.0049 8 25.38 3 3.35 18 101.00

O 2 31 13 0.0035 21 60.02 5 3.36 20 101.00

J 2 27 11 0.0033 22 60.13 3 3.35 17 101.00

E 2 20 7 0.0024 15 43.61 16 5.93 28 317.95

G 2 7 14 0.0040 6 16.26 18 7.90 26 156.12

M 1 1 26 0.0543 13 38.87 28 18.11 6 57.53

M 2 −8 25 0.0515 23 65.91 28 18.11 6 57.53

C 1 −8 30 NA 3 7.92 11 5.13 3 46.49

U 2 −17 22 0.0141 25 75.28 14 5.73 30 540.60

S 1 −18 20 0.0108 29 87.60 22 10.31 24 150.35

H 1 −19 23 0.0203 26 82.66 9 4.37 15 86.46

S 2 −20 21 0.0136 30 88.46 22 10.31 23 150.35

H 2 −21 24 0.0204 27 86.56 9 4.37 16 86.46

C 2 −28 29 NA 4 10.21 11 5.13 4 46.49

F 1 −29 27 0.0591 12 37.56 26 18.07 10 77.02

F 2 −33 27 0.0591 20 49.34 26 18.07 10 77.02

U 1 −49 19 0.0099 28 86.60 15 5.82 29 440.68

Table 96: Tabulation of operationally-ranked results for Class B — Identification Flats. Letter refers to the participant’s letter code found on the footer of

this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of the scoring

equations shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The FNIR column

was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not be performed.

The Identification column shows the time used to perform a search over an enrollment set of 3 000 000, as seen in Table 19. The Enrollment column shows

the time used to create a search template to be used for a query, as seen in Table 78. Identification and Enrollment durations are reported in seconds,

but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes over all

compute nodes after returning from the identification stage one initialization method, as seen in Table 63. RAM is reported in gigabytes, where 1 GB is

equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in green

and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
216 FPVTE – FINGERPRINT MATCHING

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

Q 1 133 2 0.0011 9 36.86 20 9.11 2 13.33

I 2 114 1 0.0010 10 38.28 30 16.99 11 110.22

D 2 108 2 0.0011 26 74.36 24 13.66 15 132.37

Q 2 102 4 0.0013 8 35.35 20 9.11 1 13.33

L 1 101 16 0.0102 3 17.51 1 3.48 23 192.19

I 1 78 4 0.0013 16 52.41 29 16.67 4 84.42

E 1 74 14 0.0088 2 12.77 11 5.20 14 127.39

J 1 66 12 0.0047 12 43.57 5 3.62 20 181.00

V 1 55 7 0.0024 14 47.02 7 3.66 13 121.80

G 1 51 23 0.0368 1 7.71 18 8.32 25 274.35

V 2 51 7 0.0024 19 62.26 7 3.66 12 121.79

L 2 39 15 0.0095 6 23.53 1 3.48 27 274.95

O 1 35 9 0.0025 23 68.54 3 3.61 19 181.00

C 2 32 24 0.0711 5 18.38 13 5.80 10 92.86

O 2 31 10 0.0027 24 73.41 3 3.61 22 181.00

H 2 23 19 0.0275 20 65.36 9 5.16 18 144.02

H 1 21 20 0.0276 21 68.07 9 5.16 17 144.02

D 1 11 6 0.0015 25 73.93 17 7.10 16 132.37

J 2 9 10 0.0027 28 77.75 6 3.62 21 181.00

G 2 3 20 0.0276 7 23.69 18 8.32 26 274.35

M 2 2 27 0.0826 13 46.70 25 15.83 8 90.93

F 1 1 25 0.0734 15 51.69 27 15.87 7 90.93

F 2 −1 25 0.0734 18 60.86 27 15.87 6 90.93

U 2 −7 17 0.0155 22 68.30 15 5.91 29 811.45

U 1 −10 18 0.0163 27 74.94 15 5.91 29 811.45

S 1 −21 22 0.0311 29 86.56 22 10.87 24 260.37

M 1 −21 28 0.0934 11 43.37 25 15.83 5 90.93

E 2 −25 13 0.0048 17 52.91 12 5.20 28 573.25

C 1 −35 30 NA 4 18.30 13 5.80 9 92.86

S 2 −94 29 0.1680 30 91.74 22 10.87 3 61.04

Table 97: Tabulation of operationally-ranked results for Class C — Ten-Finger Plain-to-Plain. Letter refers to the participant’s letter code found on the

footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of

the scoring equations shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The

FNIR column was computed at the score threshold that gave FPIR = 10−3. NA indicates that the operations required to produce the value could not

be performed. The Identification column shows the time used to perform a search over an enrollment set of 5 000 000, as seen in Table 20. The Enrollment

column shows the time used to create a search template to be used for a query, as seen in Table 79. Identification and Enrollment durations are reported in

seconds, but were originally recorded to microsecond precision. RAM refers to the sum of the resident set sizes of the stage one identification processes

over all compute nodes after returning from the identification stage one initialization method, as seen in Table 64. RAM is reported in gigabytes, where

1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the value’s column-wise ranking, with the best performance shaded in

green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology
FPVTE – FINGERPRINT MATCHING 217

Participant Score FNIR Identification Enrollment RAM

Letter Sub. #

I 2 124 2 0.0014 7 30.82 24 18.73 11 137.03

I 1 115 1 0.0013 15 54.56 25 20.23 4 113.80

Q 2 101 2 0.0014 25 74.22 17 13.06 2 20.22

V 1 90 5 0.0017 10 40.74 9 8.50 17 234.03

D 1 84 4 0.0015 17 58.92 21 17.39 10 132.40

L 2 73 14 0.0083 5 20.25 3 4.36 26 367.82

E 1 71 18 0.0106 2 8.63 12 9.92 16 191.66

Q 1 69 5 0.0017 26 74.40 17 13.06 1 20.22

L 1 66 17 0.0097 8 31.68 3 4.36 21 280.49

C 2 55 15 0.0085 6 21.97 13 10.69 15 183.36

C 1 55 16 0.0094 4 20.15 13 10.69 14 183.36

V 2 51 8 0.0019 18 65.07 9 8.50 18 234.03

G 1 49 24 0.0447 1 7.78 19 15.50 20 261.29

J 1 44 13 0.0051 9 33.02 5 6.69 22 303.13

O 1 34 11 0.0034 14 54.42 6 6.71 25 303.13

G 2 33 21 0.0333 3 19.46 19 15.50 19 261.29

O 2 32 9 0.0033 21 69.30 6 6.71 23 303.13

J 2 31 9 0.0033 19 67.98 8 6.74 24 303.13

U 2 15 22 0.0351 24 72.48 1 2.87 28 806.17

M 2 6 27 0.0716 13 48.80 26 20.89 5 130.29

E 2 4 12 0.0050 11 42.73 11 9.91 30 930.48

D 2 3 7 0.0018 27 74.97 30 30.47 9 132.37

F 1 2 25 0.0536 16 55.79 28 20.92 7 130.29

U 1 −3 23 0.0358 28 82.61 1 2.87 28 806.17

F 2 −3 25 0.0536 20 68.20 28 20.92 6 130.29

H 2 −18 19 0.0199 29 84.50 15 12.17 12 144.02

H 1 −18 20 0.0201 30 84.51 15 12.17 13 144.02

M 1 −29 28 0.0783 12 48.08 26 20.89 8 130.29

S 2 −56 30 0.2462 23 70.77 22 17.57 3 78.28

S 1 −96 29 0.0860 22 69.71 22 17.57 27 382.88

Table 98: Tabulation of operationally-ranked results for Class C — Ten-Finger Rolled-to-Rolled. Letter refers to the participant’s letter code found on

the footer of this page. Sub. # is an identifier used to differentiate between the two submissions each participant could make. Score refers to the sum of

the scoring equations shown in Appendix L. The color bands are indicative of the 80th percentile, 55th percentile, and below of the Score column. The

FNIR column was computed at the score threshold that gave FPIR = 10−3. The Identification column shows the time used to perform a search over an

enrollment set of 5 000 000, as seen in Table 20. The Enrollment column shows the time used to create a search template to be used for a query, as seen in

Table 80. Identification and Enrollment durations are reported in seconds, but were originally recorded to microsecond precision. RAM refers to the sum

of the resident set sizes of the stage one identification processes over all compute nodes after returning from the identification stage one initialization

method, as seen in Table 65. RAM is reported in gigabytes, where 1 GB is equal to 1 073 741 824 bytes. The number to the left of a value provides the

value’s column-wise ranking, with the best performance shaded in green and the worst in pink. The table is sorted on descending Score.

C = afis team D = 3M Cogent E = Neurotechnology F = Papillon G = Dermalog H = Hisign Bio-Info Institute

I = NEC J = Sonda K = Tiger IT L = Innovatrics M = SPEX O = ID Solutions

P = id3 Q = Morpho S = Decatur Industries T = BIO-key U = Aware V = AA Technology