Yooyoung Lee, Ross J. Micheals, James J. Filliben, P J. Phillips, Hassan A. Sahibzada
Due to its distinctiveness, the human eye is a popular biometricv feature used to identity a person with high accuracy. The Grand Challenge in biometrics is to have an effective algorithm for subject verification or identification under a broad range of image and environmental conditions. As a response to the challenge, this paper presents baseline performance results derived from an enhanced version of VASIR (Video-based Automated System for Iris Recognition), as well as initial performance results based on a broader ocular recognition system. We describe the details of the VASIR procedure and demonstrate its superiority over the IrisBEE baseline algorithm. We examine the relationship between VASIR performance and image quality scores. Finally, for less-contrained imaging conditions, we provide a comparison of iris and ocular recognition results.
, Micheals, R.
, Filliben, J.
, Phillips, P.
and Sahibzada, H.
Ocular and Iris Recognition Baseline Algorithm, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.IR.7828
(Accessed December 3, 2022)