Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Ocular and Iris Recognition Baseline Algorithm

Published

Author(s)

Yooyoung Lee, Ross J. Micheals, James J. Filliben, P J. Phillips, Hassan A. Sahibzada

Abstract

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.
Citation
NIST Interagency/Internal Report (NISTIR) - 7828
Report Number
7828

Keywords

Biometrics, baseline, iris recognition, ocula recognition, image quality2

Citation

Lee, Y. , Micheals, R. , Filliben, J. , Phillips, P. and Sahibzada, H. (2011), 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 October 9, 2024)

Issues

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

Created November 7, 2011, Updated November 10, 2018