Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition: The Path Forward
Computer
Score normalization in multimodal biometric systems
Pattern Recognition
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
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Iris recognition applies pattern matching techniques to compare two iris images and retrieve a comparison score that reflects their degree of (dis-)similarity. While numerous approaches to generating iris-codes have been proposed for the relatively young discipline of automated iris recognition, there are only few, usually simple, comparison techniques, e.g. fractional Hamming distance. However, in case of having access to specific iris-codes only or black-boxed feature extraction, there may be situations where improved comparison (even at potentially higher processing cost) is desirable. In this paper we present a new strategy for comparing iris-codes, which utilizes variations within comparison scores at different shift positions. We demonstrate that by taking advantage of this information, which even comes at negligible cost, recognition performance is significantly improved. The soundness of the approach is confirmed by experiments using two different iris-code based feature extraction algorithms.