NIST Fingerprint Data

Craig Watson

National Institute of Standards and Technology

Information Access Division

Image Group

January 26, 2015
Public Datasets

• 2,000 subjects with two instances

• Rolled/Single finger

• Scanned from inked fingerprint cards

• Lossless compression

• 400 from each fingerprint classification 

left/right loop, whorl, arch, tented arch

NIST Special Database 4
Public Datasets

• 2,700 subjects with two instances

• Rolled/Ten finger

• Scanned from inked fingerprint cards – some 

were printed live-scan cards

• Use same fingerprint images - Lossless (SD9) 

and WSQ (SD14) compression

• Fingerprint classification distribution not 

controlled.

NIST Special Database 9 and 14
Public Datasets

• 552 subjects with one instance

• Rolled/Ten finger

• Scanned from inked fingerprint cards – some 

were printed live-scan cards

• Lossless compression

• Concentrated on low frequency fingerprint 

classifications – arch and low count loops

NIST Special Database 10
Public Datasets

• 20 subjects

• Plain/Single finger

• 10 samples (5 male/female) for all ten finger 

positions

• Video (MPEG-2) captured off live-scan device

• Rotation and distortion

NIST Special Database 24
Public Datasets

• 258 latent cases

• Includes rolled mate

• Included minutiae points validated by latent 

examiners

• ANSI/NIST formatted records

• 500ppi (SD27) and 1000ppi (SD27a)

NIST Special Database 27 and 27a
Public Datasets

• 216 subjects (SD29) and 36 subjects (SD30) with two 

instances

• Rolled/Ten finger and plain impression (4-4-1-1)

• Scanned from inked fingerprint cards

• WSQ (SD29) and lossless (SD30) compression

• ANSI/NIST formatted records

• Fingerprint cards can be reconstructed

• 757 (SD29) and 316 (SD30) fingerprint images were 

used in SD4

NIST Special Database 29 and 30
Sample Images

SD4 SD[9, 10, 14, 29, 30]

SD[29, 30] SD[29, 30]
Sample Images

SD24 SD27
Dataset Quality

• Mostly scanned fingerprint cards

• Markings on the cards and images

• No true live-scan

• SD4 is digital video
Dataset Distribution

• Deceased Subject

• CDROM (Small Fee ~$90) / Online Samples

• Compression - Lossless and Wavelet Scalar 

Quantization (WSQ)

• Image Format Issues – IHEAD - PNG
NISTIG: Public vs. Sequestered

• Public

• Can distribute

• Smaller sample sizes (hundreds/thousands)

• Less storage capacity required

• Older data (deceased subject)

• Sequestered

• Can’t distribute

• Larger sample sizes (millions)

• Increased storage capacity required

• Operational data
Dataset Consolidation

• Ground truth errors

• Controlled capture vs. operational

• Small vs. Large sample size

• Hashed/Anonymous identification impacts 

cross dataset consolidations
Fingerprint “Flipping”

Finger Positions

Swapped

1 6

2 7

3 8

4 9

5 10

11 12

13 14
Fingerprint “Flipping”

Right Slap Left Slap
NISTIG Evaluation Model

• Public Data

• Development - Participant hardware

• Validation – Participant and NIST hardware

• Sequestered Data

• Large Scale Evaluation - NIST owned 

hardware

• Results – Published in report cards and 

public reports.
Large Scale Evaluations

• Proprietary Fingerprint Templates

• One-to-One

• Fingers – Left/Right Thumb, Index, Middle

• Impression – Plain and Rolled

• #Subjects - ~120K each for mates/nonmates

• MINEX – Interoperable Template

• One-to-One

• Fingers – Left/Right Index

• Impression – Plain

• #Subjects - ~125K each for mates/nonmates

• Fingerprint Vendor Technology Evaluation

• One-to-Many 

• Fingers – All Ten

• Impression – Rolled and Plain/Slap

• #Subjects – 1.6M, 3M, and 5M
Biometrics Evaluations at NIST

biometrics.nist.gov/evaluations

Fingerprint 

Vendor

Technology 

2003 

(fpvte@nist.gov)

Proprietary 

Fingerprint

Templates 

(pft@nist.gov)

Face 

Recognition

Vendor 

Technology

(frvt@nist.gov)

Ongoing MINEX 

(minex@nist.gov)

Face 

Recognition 

Grand Challenge 

(frgc@nist.gov)

Iris Challenge 

Evaluation 

(ice@nist.gov)

Face Recognition

Vendor Technology

(frvt2006@nist.gov)

Biometric Usability

Iris Challenge 

(ice@nist.gov)

2002

Latent Fingerprint 

Technology 

(ELFT) 

(latent@nist.gov)

MINEX II

(Match on Card, 

minexII@nist.gov)

Multiple 

Biometric Grand 

Challenge 

(mbgc@nist.gov)

Slap Fingerprint 

Segmentation 

(slapseg@nist.gov)

Minutiae Exchange 

(minex@nist.gov) 2004

2006

2003

2005

2007

2009

2008

Iris Exchange 

(irex@nist.gov)

Slap Fingerprint 

Segmentation II 

(slapseg@nist.gov)

ELFT-Extended 

Feature Sets

(latent-efs@nist.gov)

Multiple Biometric 

Evaluation

(mbe2009@nist.gov) 2010

Iris Quality 

Calibration and 

Evaluation IQCE 

(irexII@nist.gov)

MBE-Still Face

PFTII

(pft@nist.gov)2011

Iris Exchange III

(irex@nist.gov)

NIST Fingerprint 

Image Quality 

NFIQ2

(nfiq2@nist.gov)

2012

Fingerprint Vendor 

Technology 2012

(fpvte@nist.gov)

Face Recognition 

Vendor 

Technology 2012 

(frvt@nist.gov)

Iris Exchange IV

(irex@nist.gov)
Impact of Evaluations

PFT – Proprietary Fingerprint Templates

MINEX – Minutiae Exchange (Interoperable Templates)

ELFT – Latent Fingerprint

SlapSeg – Slap Fingerprint Segmentation

MBE – Still Image Face Recognition

IREX – Iris Exchange

FpVTE – Fingerprint Vendor Technology Evaluation

FRVT – Facial Recognition Vendor Test

• Current measure of biometric technology performance on 

operational/sequestered data

 Valuable to sponsors:

o Developing system procurement requirements

o Provides guidance in “who’s real”

• Competition among developers

 Evaluate performance with operational data

 Innovation – speed vs. accuracy

• Advance biometric matching technologies

• Improve implementation’s adherence to standards and 

protocols

craig.watson@nist.gov