Iris recognition based on statistical assessment of wavelet coefficients

Authors:
Xing Ming;Zhi-Hui Li;Yuan-Ning Liu;Zheng-Xuan Wang
Affiliations:
College of Computer Science and Technology, Jilin University, 2699 Qianwei Ave, Changchun, 130012 P.R. China.;College of Computer Science and Technology, Jilin University, 2699 Qianwei Ave, Changchun, 130012 P.R. China.;College of Computer Science and Technology, Jilin University, 2699 Qianwei Ave, Changchun, 130012 P.R. China.;College of Computer Science and Technology, Jilin University, 2699 Qianwei Ave, Changchun, 130012 P.R. China
Venue:
International Journal of Computer Applications in Technology
Year:
2006

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Abstract

This paper presents a new iris recognition method based on the statistical assessment of wavelet coefficients. For the matrix of wavelet coefficients generated by the one-dimensional wavelet multi-scale decomposition, the method presented uses statistical assessment to determine the significant wavelet coefficients at different scales and then transforms them into a binary vector to represent the iris features. The Hamming distance classifier is adopted to perform pattern matching between an input iris image and an enrolment template. The final experiments show promising results for iris recognition.