Experiments with an Improved Iris Segmentation Algorithm
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Approach to Deformed Pattern Matching of Iris Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
An Effective Approach for Iris Recognition Using Phase-Based Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pupil dilation degrades iris biometric performance
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimizations in iris recognition
Optimizations in iris recognition
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Circuits and Systems for Video Technology
Towards long term data quality in a large scale biometrics experiment
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Iris recognition failure over time: The effects of texture
Pattern Recognition
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We explore the effects of time lapse on iris biometrics using a data set of images with four years time lapse between the earliest and most recent images of an iris (13 subjects, 26 irises, 1809 total images). We find that the average fractional Hamming distance for a match between two images of an iris taken four years apart is statistically significantly larger than the match for images with only a few months time lapse between them. A possible implication of our results is that iris biometric enrollment templates may undergo aging and that iris biometric enrollment may not be "once for life." To our knowledge, this is the first and only experimental study of iris match scores under long (multi-year) time lapse.