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Robust Iris Recognition Baseline for the Occular Challenge

Published

Author(s)

Yooyoung Lee, Ross J. Micheals, James J. Filliben, P J. Phillips

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 Title
Proceedings of the 9th IEEE Conference on Automatic Face and Gesture Recognition 2011 (FG2011)
Conference Dates
March 21-23, 2011
Conference Location
Santa Barbara, CA

Keywords

biometrics, iris recognition, VASIR, baseline, benchmarking, Hamming distance, image processing

Citation

Lee, Y. , Micheals, R. , Filliben, J. and Phillips, P. (2011), Robust Iris Recognition Baseline for the Occular Challenge, Proceedings of the 9th IEEE Conference on Automatic Face and Gesture Recognition 2011 (FG2011), Santa Barbara, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=907175 (Accessed June 20, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created January 20, 2011, Updated February 19, 2017