Abstract
The biometric template protection system requires a high-quality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that the system is robust and accurate, and to allow a secret key to be combined for security. In this paper we present a binary palmprint feature extraction method to achieve a robust biometric channel for template protection system. The real-valued texture statistical features are firstly extracted based on Gabor magnitude and phase responses. Then a bits quantization and selection algorithm is introduced. Experimental results on the HongKong PloyU Palmprint database verify the efficiency of our method which achieves low verification error rate by a robust palmprint binary representation of low bit error rate.
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© 2012 Springer-Verlag Berlin Heidelberg
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Mu, M., Ruan, Q., Shao, X., Spreeuwers, L., Veldhuis, R. (2012). Binary Gabor Statistical Features for Palmprint Template Protection. In: Gimel’farb, G., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2012. Lecture Notes in Computer Science, vol 7626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34166-3_65
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DOI: https://doi.org/10.1007/978-3-642-34166-3_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34165-6
Online ISBN: 978-3-642-34166-3
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