Iris recognition based on quadratic spline wavelet multi-scale decomposition

Authors:
Xing Ming;Xiaodong Zhu;Zhengxuan Wang
Affiliations:
Department of Computer Science and Technology, Jilin University, Changchun, China;Department of Computer Science and Technology, Jilin University, Changchun, China;Department of Computer Science and Technology, Jilin University, Changchun, China
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

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Abstract

This paper presents an efficient iris recognition method based on wavelet multi-scale decompositions. A two-dimensional iris image should be transformed into a set of one-dimensional signals initially and then the wavelet coefficients matrix is generated by one-dimensional quadratic spline wavelet multi-scale decompositions. From the basic principles of probability theory, the elements at the same position in different wavelet coefficients matrices can be considered as a high correlated sequence. By applying a predetermined threshold, these wavelet coefficients matrices are finally transformed into a binary vector to represent iris features. The Hamming distance classifier is adopted to perform pattern matching between two feature vectors. Using an available iris database, final experiments show promising results for iris recognition with our proposed approach.