Contact-Less palm vein recognition based on wavelet decomposition and partial least square

  • Authors:
  • Wei Wu;Wei-qi Yuan;Jin-yu Guo;Sen Lin;Lan-tao Jing

  • Affiliations:
  • Computer Vision Group, Shenyang University of Technology, Shenyang, China, Information Engineering Department, Shenyang University, Shenyang, China;Computer Vision Group, Shenyang University of Technology, Shenyang, China;Information Engineering Department, Shenyang University of Chemical Technology, Shenyang, China;Computer Vision Group, Shenyang University of Technology, Shenyang, China;Computer Vision Group, Shenyang University of Technology, Shenyang, China

  • Venue:
  • CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
  • Year:
  • 2012

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Abstract

To solve the problem of low recognition performance caused by contact-less imaging and poor palm vein image quality, a novel recognition method is proposed. Firstly, the ROI based on the thenar (a part of palm) is located; secondly, the palm vein features based on wavelet decomposition and partial least square are extracted; finally, the images are matched by Euclidean distance. In self-build palm vein database, the experimental result shows that the best recognition rate of this method reaches 99.86%. Comparing with the other typical palm vein recognition methods, the performance of proposed approach is the best. In conclusion, the scheme can improve the identification performance of contact-less palm vein recognition significantly.