Palmprint Recognition Using Data Field and PCNN

  • Yanxia Wang
  • Jianmin Zhao
  • Guanghua Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8251)


In this paper, an approach is proposed for palmprint recognition, which uses PCNN and data field theory to extract local statistical structure features of a palmprint. In the method, the data field theory is firstly introduced to obtain a relative palmprint data field, which enhances the palm line information. Then the relative data field is input into a PCNN. Next, the local statistical structure features with four values are extracted from each sub-region. At last, all of local statistic-structural feature vectors are weighted and combined into a long feature vector to represent the palmprint. Experiments show that the novel features can effectively characterize different palmprints.


Palmprint recognition data field PCNN feature extraction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yanxia Wang
    • 1
  • Jianmin Zhao
    • 1
  • Guanghua Sun
    • 1
  1. 1.College of Mathematics, Physics and Information EngineeringZhejiang Normal UniversityJinhuaChina

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