Binary Gabor Statistical Features for Palmprint Template Protection

  • Meiru Mu
  • Qiuqi Ruan
  • Xiaoying Shao
  • Luuk Spreeuwers
  • Raymond Veldhuis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)

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.

Keywords

Palmprint verification Binary feature extraction Feature template protection Gabor filtering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Meiru Mu
    • 1
    • 2
  • Qiuqi Ruan
    • 1
    • 2
  • Xiaoying Shao
    • 1
    • 2
  • Luuk Spreeuwers
    • 1
    • 2
  • Raymond Veldhuis
    • 1
    • 2
  1. 1.Institute of Information ScienceBeijing Jiaotong UniversityBeijingChina
  2. 2.Systems and Signals GroupUniversity of TwenteEnschedeThe Netherlands

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