evaluation of latent fingerprint technologies (elft)

Evaluation of Latent Fingerprint Technologies (ELFT)

What are Latents?

Ubiquitous (found on almost all surfaces)

Residual marks from fingers & palms

… but from Very High Value Subjects

Arbitrarily poor quality

Also toe and footprints (all friction ridge skin)

Conventional Fingerprints (not latents)

Rolls

Slaps (Flats)

Rolls

Captured Fingerprints

Flat impression

Latent Fingerprint (powder lift) Rolled Impression

Latent vs. Conventional Prints

Why Are Latents Difficult?

Tips Smudges Weathering

Why Are Latents Important?

Homeland Security

Military & Intelligence Law Enforcement / Criminal Justice

List of Candidates

Output

Rank Subject

ID

Candidate

Print

1 0733091

2 1304033

3 3952340

…

20 0847121

Automated Fingerprint Identification System

(AFIS)

Latent Examiner

Image + features (for comparison)

Ma

rk

Image + features (for search)

Input

Ma

rk

Mark

/ C

om

pare

Latent Examiner

Ma

rk / C

om

pa

re

Mrk

/Co

mp

Match

Latent AFIS Technology

Latent AFIS Technology Problems?

Manual workload …

Indeterminate

Bifurcation

AFIS ID step: Manual Feature Markup

Core

Core

Ridge

ending

Examiner & Workstation

Latent Workstation Screenshot

Latent AFIS Technology Problems?

Manual processing …

Accuracy …

0

10

20

30

40

50

60

70

80

90

100

�Identification Rate (%)

Conventional AFIS

Latent AFIS

37%

Conventional vs. Latent ID Rates

Latent AFIS Technology Problems?

Manual processing …

Accuracy …

Interoperability …

AFIS Interoperability: Now

AFIS Interoperability: Future

Core

Indeterminate

Incipient

Pore Core

Ridge

ending

Protrusion

Bifurcation

Improved Feature Quality o ridge 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)

What is ELFT?

• Open evaluation of Automated Latent Fingerprint Identification Systems (AFIS) using automatic feature extraction and matching and standardized features hand-marked by human experts (EFS).

• Interactive effort between NIST and latent AFIS community to improve accuracy, promote interoperability, and reduce reliance on human examiners.

Acquire Latent

Matchers (SDKs)

Configure Hardware

Compile Latent Test Sets

ELFT Testing Architecture

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

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 History

Measured Accuracy Improvement

(ELFT-EFS 1 vs. 2)

Customers and Community

Industry Academia

Developers & Researchers:

• Measurement & failure analysis

• Reference data

Government Law Enforcement

• Standards

Users & Practitioners:

• Performance rankings

• System integration & tuning

• Standards

• Conferences, Journals

• Conferences, Workshops

Path Forward

Develop best practices to reduce manual workload • lights-out processing of some operational workload • searching and encoding strategies • quality metrics

Evaluate state-of-the-art latent fingerprint and (new) palmprint AFIS • interoperability testing (LITS/EFS profiles) • matcher and data fusion • candidate reduction techniques

Expand scale of ELFT testing

•operational scale tests •operational vs. research algorithms

Questions?