Volume 34 Issue 03
Mar.  2008
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Chen Zhi, Huang Linlin. Palmprint recognition based on ICA and BP neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(03): 290-294. (in Chinese)
Citation: Chen Zhi, Huang Linlin. Palmprint recognition based on ICA and BP neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(03): 290-294. (in Chinese)

Palmprint recognition based on ICA and BP neural network

  • Received Date: 29 Jun 2007
  • Publish Date: 31 Mar 2008
  • A novel method based on independent comment analysis (ICA) and back propagation neural network (BPNN) was proposed to solve palmprint recognition. First, a new method was used to detect corner points as the invariant feature points in palm images. Then the palm images were aligned by the points, and the region of interest (ROI) of the images was gotten. In the next place, palmprint features were extracted from the ROI by a fast fixed-point algorithm for ICA (FastICA). By means of this method, the original palmprint ROI images were transformed into a small set of feature space. Finally, the BPNN was trained by the feature spaces of the samples in the training set to get the appropriate weights. After the training, perform palm classification was applied. The method was tested on the Hong Kong Polytechnic University palmprint database. Experimental results show that method based on ICA achieves higher recognition rate than that based on principal components analysis (PCA).

     

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