A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition

  • Tuo Zhao
  • Zhizheng Liang
  • David Zhang
  • Yahui Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetrical objects. In this paper, a novel null space kernel discriminant method based on the symmetrical method with a weighted fusion strategy is proposed for face recognition. It can effectively enhance the recognition performance and shares the advantages of Null-space, kernel and symmetrical methods. The experiment results on ORL database and FERET database demonstrate that the proposed method is effective and outperforms some existing subspace methods.


symmetrical decomposition symmetrical null-space based kernel LDA weighted fusion strategy face recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Tuo Zhao
    • 1
  • Zhizheng Liang
    • 1
  • David Zhang
    • 2
  • Yahui Liu
    • 1
  1. 1.Harbin Institute of Technology 
  2. 2.Hongkong Polytechnic University 

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