Developments in Latent 

Fingerprint Technologies 

Evaluation of Latent Fingerprint Technologies (ELFT) Project

 

28 September 2011 

Vladimir Dvornychenko 

Michael Indovina 
Information Access Division 2 

Rolled Fingerprint 

(ink capture) 

Latent Fingerprint 

(ink capture) (powder lift) 

Plain Fingerprint 
 2006 NIST Latent Fingerprint Testing Workshop 

 2007 ELFT Phase I Evaluation 

 2008 ELFT Phase II Evaluation 

 2009 NIST Latent Fingerprint Testing Workshop 

 ELFT Phase II Miss Analysis Sessions 

 ELFT-EFS Public Challenge 

 2010 ELFT-EFS Evaluation #1 

 ELFT-EFS Miss Analysis Sessions 

 2011 ELFT-EFS Evaluation #2 

ELFT Project Timeline 
Acquire Latent 

Matchers (SDKs) 

Configure Hardware 

Compile Latent Test Sets 

NIST Evaluation of Latent Fingerprint 

Technologies (ELFT) o Execute 1-to-Many searches 

• Image-only searches 

• Examiner-assisted searches 

 (image + feature markup) 

• Operational images 

• Extended Feature Sets 

o Measure & Analyze Results 

• Accuracy 

• Selectivity 

• Resource requirements 

• Gap analysis 

Iterate process 

1. Evaluation Reports 

2. Feedback to Standardization 

3. Technological Gap Analysis 

4. Reference Data 

Evaluation Protocol 
Latent image 

(+ features) 

“Search”

Latent Examiner 

Ran

k Candidate 

1 

2 

3 

...

20

Potential 

 matches 

 AFIS 
0

10

20

30

40

50

60

70

80

90

100

Identification Rate (%)

Conventional AFIS

Latent AFIS

fewer 

identifications 

Latent AFIS Technology Gaps: 

Relatively Low Accuracy 
Latent AFIS Technology Gaps 

 Relatively low accuracy 

• 65-70% identification rate considered “high performance”

 High manual workload 

• features selection & markup 

• candidate list evaluation 

Solution: Measurement and evaluation of searches using 

image only (“lights out”) vs. manually assisted search 

performance, and evaluation of candidate list reduction 

methods. 
Number of Minutiae 

Accuracy 

ELFT Results: 

“Lights out” vs Manual Feature Selection 
Average Number of Candidates 

Accuracy 

ELFT Results: 

Accuracy vs. Examiner Workload 
Latent AFIS Technology Gaps 

 Limited interoperability 

• best accuracy requires manual feature selection/markup 

• commercial AFIS use non-standard features 

• even the same features vary between AFIS 

• no universal standard for feature selection/markup 

• features re-selected/marked for each new AFIS searched 

Solution: Develop a comprehensive set of features which can 

be used to build a universal set of latent fingerprint search 

transactions. Latent Interoperability Transmission Specification 

(LITS) based on ANSI/NIST-ITL 2011 which includes Extended 

Feature Sets (EFS) and FBI EBTS. 
11 Michael Indovina 

IAD - Image Group 

AFIS Interoperability: Now 
12 Michael Indovina 

IAD - Image Group 

AFIS Interoperability: Future 
Core 

Indeterminate 

Incipient 

Pore 

Core 

Ridge 

ending 

Protrusion 

Bifurcation 

 Improved Feature Quality 

o region quality map 

 Improved Feature Set: 

o endings/bifurcations 

Dot 

o pores 

o protrusions 

o incipient ridges 

o dots 

o creases 

o scars 

o skeleton 

Extended Feature Set (EFS)
14

EFS Evaluation & Testing 

 ELFT-EFS Evaluation #1 

• 1st Multi-vendor AFIS matcher evaluation using a common feature set (EFS) 

• Features defined by upcoming ANSI/NIST-ITL 2011 standard 

• Feature marked by experienced latent examiners using a common guidelines 

• Assesses the performance of latent AFIS search technology with: 

 minutiae only 

 image only 

 image + various subsets of EFS 

• Final Report: NISTIR 7775, March 2011 

 ELFT-EFS Evaluation #2 

• Re-iteration of Evaluation #1 with updated algorithms 

• Follows miss analysis sessions conducted with developers 

• Measures improvements/regressions in matcher performance 

• Provides better estimate of state of the art 

• Final Report TBD October 2011 

 
ELFT-EFS Results: 

Accuracy vs. EFS Feature Subset 
ELFT-EFS Results: 

Accuracy Improvement (Eval 1 vs. 2) 
 ELFT-LITS (start date to be announced Fall 2011) 

• LITS = Latent Interoperability Transmission Specification (LITS) 

• evaluation of LITS based search transaction performance 

 ELFT-PALM (start date to be announced Fall 2011)

• evaluation of AFIS performance for latent palm vs. enrolled palm 

Future Work 

 Future ELFT evaluations will also evaluate: 

• high-, medium-, and low-resource algorithm performance tradeoffs 

• “reverse latent” (rolled-/plain-print to enrolled latent) matching 

performance 

• fusion approaches to enhancing performance 
For More Information...

 Web  http://fingerprint.nist.gov/latent

 Email  latent-efs@nist.gov 

18 Michael Indovina 

IAD - Image Group 
19 Michael Indovina 

IAD - Image Group 

Presentation Overview 

1. Introduction to automated latent print ID 

2. Automated latent ID technology (AFIS) 

3. Latent AFIS technology gaps 

4. NIST latent testing & evaluation (ELFT) 
September 2009 20 Michael Indovina 

IAD - Image Group 

Automated Latent Fingerprint 

Identification Systems 

(AFIS) 
September 2009 21 Michael Indovina 

IAD - Image Group 

Latent workstation 

Latent matching unit & database 

(AKA “AFIS”)
Information Access Division 22

Homeland Security 

Law Enforcement / Criminal Justice Military & Intelligence 
September 2009 23 Michael Indovina 

IAD - Image Group 

Collective Matcher Performance 

 (1,114 latents) 
24

Indeterminate 

Bifurcation 

Core 

Core 

Ridge 

ending 

Latent Examiner 

Latent Workstation Screenshot 
September 2009 25 Michael Indovina 

IAD - Image Group 

Roadblocks to Interoperability 

 Lack of cross-jurisdictional interconnectivity 

• technological differences 

• lack of exchange processes/agreements 

• funding issues, usage policies, legal issues, ...

 Variation in feature selection, markup, and exchange 

• best accuracy requires hand-marked features 

• lack of universal standard for data exchange 

• additional AFIS searches = additional examiner workload 
May 2010 26

Solutions 

 Improve AFIS accuracy 

• testing & evaluation to analyze performance/gaps 

• standard reference data for developers 

 Develop interoperable latent search features 

• based on ANSI/NIST-ITL EFS and FBI EBTS (LITS) 

• assess accuracy and utility of interoperable features 

 Reduce the need for manual processing 

• determine where “lights out” processing is viable

• improved selectivity (fewer/better candidates) 
Accuracy 

Number of Minutiae 

ELFT-EFS Results: 

Accuracy vs. Minutiae Count