Evaluating the information content of near-infrared iris imagery

Authors:
Robert W. Ives;Hau Ngo;Stephen Winchell
Affiliations:
US Naval Academy, Annapolis, MD;US Naval Academy, Annapolis, MD;US Naval Academy, Annapolis, MD
Venue:
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Year:
2011

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High Confidence Visual Recognition of Persons by a Test of Statistical Independence

IEEE Transactions on Pattern Analysis and Machine Intelligence

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Abstract

The human iris exhibits random and unique textural patterns that allow for identification with high accuracy. These patterns are evident in near-infrared (NIR) imagery, even for very dark irises. The authors investigate the information content of the iris contained in these patterns, and how it affects recognition performance. In this paper, iris templates are created from NIR iris imagery with the Ridge Energy Direction (RED) recognition algorithm, and using common biometric performance metrics we determine which portions of the iris contain the most distinctive information for recognition.