Ten lectures on wavelets
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition Using Wavelet Features
Journal of VLSI Signal Processing Systems
Iris Recognition Using Collarette Boundary Localization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Iris quality assessment and bi-orthogonal wavelet based encoding for recognition
Pattern Recognition
A novel biorthogonal wavelet network system for off-angle iris recognition
Pattern Recognition
Reliable algorithm for iris segmentation in eye image
Image and Vision Computing
The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Guide to Biometrics
Graph matching iris image blocks with local binary pattern
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
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
IEEE Transactions on Circuits and Systems for Video Technology
The results of the NICE.II Iris biometrics competition
Pattern Recognition Letters
A review of information fusion techniques employed in iris recognition systems
International Journal of Advanced Intelligence Paradigms
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This article describes an iris recognition algorithm designed to analyze noisy iris biometric data. The methods forming part of the authentication process were developed and optimized by the authors using visible wavelength images of an eye taken under unconstrained conditions (at a different perspectives, illuminations, occlusion grades, etc.), mainly contained in the UBIRIS.v2 database. The whole iris authentication system was submitted by the authors to the International Iris Recognition Contest NICE.II, where it took eighth place, while the iris segmentation stage itself took second place in the previous contest - NICE.I. This paper is focused on the iris feature extraction stage - the method developed by the authors to analyze noisy iris biometric data. Several techniques used for more efficient and robust analysis of such images and issues concerning the best wavelet selection are also presented in this paper.