Fake iris detection based on multiple wavelet filters and hierarchical SVM

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Abstract

With the increasing needs for higher security level, biometric systems have been widely used for many applications. Among biometrics, iris recognition system has been in the limelight for high security applications. Until now, most researches have been focused on iris identification algorithm and iris camera system. However, after the recent report of attacking iris recognition system by fake iris such as printed, photography and contact lens iris has been disclosed, the importance of fake iris detection is much increased. So, we propose the new method of detecting fake iris. This research has following three advances compared to previous works. First, to detect fake iris, we check both the size change of pupil and the change of iris features in local iris area (near pupil boundary) by visible light. Second, to detect the change of local iris features, we used multiple wavelet filters having Gabor and Daubechies bases. Third, to enhance the detecting accuracy of fake iris, we used a hierarchical SVM (Support Vector Machine) based on extracted wavelet features. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Park, K. R., Whang, M. C., Lim, J. S., & Cho, Y. (2006). Fake iris detection based on multiple wavelet filters and hierarchical SVM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4296 LNCS, pp. 246–256). Springer Verlag. https://doi.org/10.1007/11927587_21

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