Empirical study of light source selection for palmprint recognition

  • Authors:
  • Zhenhua Guo;David Zhang;Lei Zhang;Wangmeng Zuo;Guangming Lu

  • Affiliations:
  • Graduate School at Shenzhen, Tsinghua University, Shenzhen, China;Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2011

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Abstract

Most of the current palmprint recognition systems use an active light to acquire images, and the light source is a key component in the system. Although white light is the most widely used light source, little work has been done on investigating whether it is the best illumination for palmprint recognition. This study analyzes the palmprint recognition performance under seven different illuminations, including the white light. The experimental results on a large database show that white light is not the optimal illumination, while yellow or magenta light could achieve higher palmprint recognition accuracy than the white light.