Robust Iris Recognition Baseline for the Occular Challenge
Yooyoung Lee, Ross J. Micheals, James J. Filliben, P J. Phillips
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 of the 9th IEEE Conference on Automatic Face and Gesture Recognition 2011 (FG2011)
, Micheals, R.
, Filliben, J.
and Phillips, P.
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 December 9, 2023)