Abstract
This paper presents an effective iris recognition system for iris localization, feature extraction, and matching. By combining the shift-invariant and the multi-resolution properties from Fourier descriptor and wavelet transform, the Fourier-Wavelet features are proposed for iris recognition. A similarity measure is adopted as the matching criterion. Four wavelet filters containing Haar, Daubechies-8, Biorthogonal 3.5, and Biorthogonal 4.4 are evaluated and they all perform better than the feature of Gaussian-Hermite moments. Experimental results demonstrate that the proposed features can provide promising performance for iris recognition.
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© 2005 Springer-Verlag Berlin Heidelberg
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Huang, P.S., Chiang, CS., Liang, JR. (2005). Iris Recognition Using Fourier-Wavelet Features. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_2
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DOI: https://doi.org/10.1007/11527923_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27887-0
Online ISBN: 978-3-540-31638-1
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