Binary gabor statistical features for palmprint template protection

Meiru Mu, Qiuqi Ruan, X. Shao, Lieuwe Jan Spreeuwers, Raymond N.J. Veldhuis

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


    The biometric template protection system requires a highquality 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.
    Original languageUndefined
    Title of host publicationJoint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012)
    Place of PublicationBerlin
    Number of pages9
    ISBN (Print)978-3-642-34165-6
    Publication statusPublished - 7 Nov 2012

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag


    • SCS-Safety
    • EWI-22989
    • Palmprint verification
    • IR-83638
    • Gabor filtering
    • Feature template protection
    • METIS-296445
    • Binary feature extraction

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