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Face Recognition Using Improved-LDA

  • Dake Zhou
  • Xin Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3212)

Abstract

This paper introduces an improved-LDA (I-LDA) approach to face recognition, which can effectively deal with the two problems encountered in LDA-based face recognition approaches: 1) the degenerated generalization ability caused by the “small sample size” problem, and 2) Fisher criterion is nonoptimal with respect to classification rate. In particular, the I-LDA approach can also improve the classification rate of one or several appointed classes by using a suitable weighted scheme. The key to this approach is to use the direct-LDA techniques for dimension reduction and meanwhile utilize a modified Fisher criterion that it is more closely related to classification error. Comparative experiments on ORL face database verify the effectiveness of the proposed method.

Keywords

Face Recognition Linear Discriminant Analysis Face Image Scatter Matrix Fisher Criterion 
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 2004

Authors and Affiliations

  • Dake Zhou
    • 1
  • Xin Yang
    • 1
  1. 1.Institute of Image Processing & Pattern RecognitionShanghai Jiaotong UniversityShanghaiChina

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