Palmprint identification using feature-level fusion

  • Authors:

  • Adams Kong;David Zhang;Mohamed Kamel

  • Affiliations:

  • Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong and Pattern Analysis and Machine Intelligence Lab, University of Waterloo, On ...;Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Pattern Analysis and Machine Intelligence Lab, University of Waterloo, Ont., Canada N2L 3G1

  • Venue:
  • Pattern Recognition
  • Year:
  • 2006

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Abstract

In this paper, we propose a feature-level fusion approach for improving the efficiency of palmprint identification. Multiple elliptical Gabor filters with different orientations are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A dynamic threshold is used for the final decisions. A database containing 9599 palmprint images from 488 different palms is used to validate the performance of the proposed method. Comparing our previous non-fusion approach and the proposed method, improvement in verification and identification are ensured.