| 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: |
 Click here to retrieve PDF version of paper (926KB) |
