Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns
International Journal of Computer Vision
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comments on the CASIA version 1.0 Iris Data Set
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris recognition by local extremum points of multiscale Taylor expansion
Pattern Recognition
Iris feature extraction using independent component analysis
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A phase-based iris recognition algorithm
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
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Random distribution of features in iris image texture allows to perform iris-based personal authentication with high confidence. We propose to use the most significant local extremum points of the first two Taylor expansion coefficients as descriptors of the iris texture. A measure of similarity that is robust to moderate inaccuracies in iris segmentation is presented for the proposed features. We provide experimental results of verification quality for four commonly used iris data-sets. Strong and weak aspects of the proposed approach are also discussed.