Abstract
In general, the iris recognition systems have used the wavelet transform as feature extraction techniques. Since the wavelet transform does not have the shift-invariant property, the iris features are inconsistently extracted due to the eye image rotation and the inexact iris localization. In this paper, a novel method to extract features is proposed for iris recognition system. Two types of features are obtained from the discrete wavelet frame decomposition. The first one is the global feature which is insensitive to the iris image deformation. The second one is the local feature which can represent the iris local texture. If the global distance between the test image and the stored one in the database is smaller than the threshold value, it is added to the candidates. And then, local matching is performed by Hamming distance. Experimental results show the proposed system could be used for the personal recognition efficiently.
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References
John G. Daugman: High confidence visual recognition of personals by a test of statistical independence. IEEE Trans. Pattern Anal. Machine Intell., Vol. 15, no. 11, pp.1148–1160, November 1993.
Richard P. Wildes: Iris Recognition: An Emerging Biometric Technology. Proceedings of The IEEE, Vol. 85, No. 9, pp.1348–1363, September 1997.
W.W. Boles and B. Boashash: A human Identification Technique Using Images of the Iris andWavelet Transform. IEEE Transactions On Signal Processing, Vol. 46, no. 4, pp.1185–1188, April 1998.
Sergios Theodoridis and Konstantinos Koutroumbas: Pattern Recognition, Academic Press, 1999.
Stephane Mallat: Zero-Crossing of a Wavelet Transform. IEEE Trans. Information Theory, Vol. 37, No. 4, pp.1019–1033, July 1991.
Christel-loic Tisse, Lionel Martin, Lionel Torres, and Michel Robert: Person Identification Technique Using Human Iris Recognition. The 15th International Conference on Vision Interface, pp.294–299, May 27–29, 2002, Calgary, Canada.
Jane You, Wenxin, and David Zhang: Hierarchical Palmprint Identification via Multiple Feature Extraction. Pattern Recognition, Vol. 35, pp.847–859, 2002.
Michael Unser: Texture Classification and Segmentation Using Wavelet Frames. IEEE Trans. Image Processing, Vol. 4, No. 11, pp.1549–1560, November 1995.
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© 2003 Springer-Verlag Berlin Heidelberg
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Seung-In, N., Bae, K., Park, Y., Kim, J. (2003). A Novel Method to Extract Features for Iris Recognition System. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_100
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DOI: https://doi.org/10.1007/3-540-44887-X_100
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