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Palmprint Recognition Based on Directional Features and Graph Matching

  • Yufei Han
  • Tieniu Tan
  • Zhenan Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

Palmprint recognition, as a reliable personal identity check method, has been receiving increasing attention during recent years. According to previous work, local texture analysis supplies the most promising framework for palmprint image representation. In this paper, we propose a novel palmprint recognition method by combining statistical texture descriptions of local image regions and their spatial relations. In our method, for each image block, a spatial enhanced histogram of gradient directions is used to represent discriminative texture features. Furthermore, we measure similarity between two palmprint images using a simple graph matching scheme, making use of structural information. Experimental results on two large palmprint databases demonstrate the effectiveness of the proposed approach.

Keywords

Graph Match Palmprint Image Palmprint Recognition Local Image Region Palmprint Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yufei Han
    • 1
  • Tieniu Tan
    • 1
  • Zhenan Sun
    • 1
  1. 1.Center for Biometrics and Security Research, National Labrotory of Pattern Recognition,Institue of Automation, Chinese Acdamey of Sciences, P.O. Box 2728, Beijing, 100080P.R. China

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