![Page 1: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/1.jpg)
Biometric Measures for Human Identification
D. Adjeroh, B. Cukic, L. Hornak, A. Ross
Lane Department of CSEEWest Virginia University
NC-BSI, December 2008
![Page 2: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/2.jpg)
NC – BSI 2008 2
Problem Statement
• Current biometric systems at the US borders rely on fingerprint and face recognition (US-VISIT). We will analyze the use of other biometric modalities (iris, palm, face, voice) and their combinations for border security.
• Methodology– Lab and field experiments to study the maturity,
reliability, cost, performance, and feasibility of new biometric modalities in the context of border security.
![Page 3: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/3.jpg)
NC – BSI 2008 3
Risk function
Systems Approach: Port of Entry
Traveler Queues
Watch Lists / Identity DB
Legend=Required Signal=Optional Signal= Movement
Public Key Directory
Secondary Inspection / Detainment
Border Access
=Optional Movement
Inspection Stations(w/ biometric )
after Cukic et al.after Cukic et al.
Local, distributed, or central?
Modality, quality, scalability, update, access ?
Acceptance,modality, quality?
Modality, FMR, vulnerability, exceptions, throughput?
False Match Rate, Inconvenience acceptance?
False Non Match Rate
![Page 4: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/4.jpg)
NC – BSI 2008 4
Error RatesError Rates
Test Test ParameterFalse Reject
Rate False Accept
Rate
Fingerprint
FVC[2004]
Exaggerated distortion 2% 2%
FpVTE[2003]
US govt. operational data
0.1% 1%
Face
FRVT[2002]
Varied lighting, outdoor/indoor
10% 1%
FRGC[2006]
Time lapse, varied lighting/expression,
outdoor/indoor10% 0.1%
IrisITIRT
[2005] Indoor environment,
multiple visits0.99% 0.94%
VoiceNIST
[2004]Text independent,
multi-lingual5-10% 2-5%
![Page 5: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/5.jpg)
NC – BSI 2008 5
NIST FRVT 2006 Results
![Page 6: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/6.jpg)
NC – BSI 2008 6
Sensor InteroperabilitySensor Interoperability
A. Ross and R. Nadgir, "A Calibration Model for Fingerprint Sensor Interoperability", Proc. of SPIE Conference on Biometric Technology for Human Identification III, (Orlando, USA), April 2006.
![Page 7: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/7.jpg)
NC – BSI 2008 7
Multimodal Biometric Systems
• Multiple sources of biometric information are integrated to enhance matching performance
• Increases population coverage by reducing failure to enroll rate
• Anti-spoofing; difficult to spoof multiple traits simultaneously
Fingerprint Face Hand geometry Iris
![Page 8: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/8.jpg)
NC – BSI 2008 8
Deployment Problems
• Sensor Interoperability• Missing information from some modalities• Non-ideal capture
– Non-cooperative subjects or capture problems– surveillance scenarios, i.e., identifying risk early
• Varying risk tolerance• Maximizing identification rates while minimizing
inconvenience and disruption of border crossing flow.
![Page 9: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/9.jpg)
NC – BSI 2008 9
Leverage
• The Center for Identification Technology Research (NSF I/UCRC)
• Biometrics: Performance, Security and Social Impact, (NSF and DHS – Human Factors)• Performance analysis, multimodal biometric database
collections, familiarity with port of entry applications. • WVU is academic partner with the FBI Center of
Excellence in Biometrics• Large scale data collection for the New Generation Identification
project.
![Page 10: Biometric Measures for Human Identification D. Adjeroh, B. Cukic, L. Hornak, A. Ross Lane Department of CSEE West Virginia University NC-BSI, December](https://reader036.vdocuments.net/reader036/viewer/2022062517/56649ee15503460f94bf17ad/html5/thumbnails/10.jpg)
NC – BSI 2008 10
Deliverables
• Year 1:– Analysis of existing performance studies, – Defining specific border application scenarios and their
requirements, – Definition of lab experiments – Definition of field experiments.
• Years 2-5:– Experimental results – Modality recommendations – Multi-modal fusion, – System aspects and recommendations.