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Publication Citation: Robust Iris Recognition Baseline for the Occular Challenge

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Author(s): Yooyoung Lee; Ross J. Micheals; James J. Filliben; P J. Phillips;
Title: Robust Iris Recognition Baseline for the Occular Challenge
Published: January 20, 2011
Abstract: Due to its distinctiveness, the human iris is a popular biometric feature used to identity a person with high accuracy. The Grand Challenge in iris recognition is to have an effective algorithm for subject verification or identification under a broad range of image and environmental conditions. This paper presents VASIR (Video-based Automated System for Iris Recognition) as a response to such a challenge. We describe the details of the VASIR procedure and show its superiority over the IrisBEE algorithm. We also demonstrate the effectiveness of the automated best-image-selection component and give details of VASIR s performance as a baseline/benchmark. Finally, our image quality scores and how they relate to VASIR s performance are examined.
Proceedings: Proceedings of the 9th IEEE Conference on Automatic Face and Gesture Recognition 2011 (FG2011)
Pages: 9 pp.
Location: Santa Barbara, CA
Dates: March 21-23, 2011
Keywords: biometrics, iris recognition, VASIR, baseline, benchmarking, Hamming distance, image processing
Research Areas: Biometrics
PDF version: PDF Document Click here to retrieve PDF version of paper (948KB)