A Multi-Sample Standoff Multimodal Biometric System

Conference · Sun Jan 01 04:00:00 EST 2012

OSTI ID:1056936

Barstow, Del R ^[1]; Patlolla, Dilip Reddy ^[1]; Mann, Christopher J ^[1]; Boehnen, Chris Bensing ^[1]

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1. ORNL

Abstract The data captured by existing standoff biometric systems typically has lower biometric recognition performance than their close range counterparts due to imaging challenges, pose challenges, and other factors. To assist in overcoming these limitations systems typically perform in a multi-modal capacity such as Honeywell s Combined Face and Iris (CFAIRS) [21] system. While this improves the systems performance, standoff systems have yet to be proven as accurate as their close range equivalents. We will present a standoff system capable of operating up to 7 meters in range. Unlike many systems such as the CFAIRS our system captures high quality 12 MP video allowing for a multi-sample as well as multi-modal comparison. We found that for standoff systems multi-sample improved performance more than multi-modal. For a small test group of 50 subjects we were able to achieve 100% rank one recognition performance with our system.

• Research Organization: Oak Ridge National Laboratory (ORNL)
• Sponsoring Organization: ORNL work for others
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1056936
• Country of Publication: United States
• Language: English