An Uncorrelated Fisherface Approach for Face and Palmprint Recognition

  • Xiao-Yuan Jing
  • Chen Lu
  • David Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)


The Fisherface method is a most representative method of the linear discrimination analysis (LDA) technique. However, there persist in the Fisherface method at least two areas of weakness. The first weakness is that it cannot make the achieved discrimination vectors completely satisfy the statistical uncorrelation while costing a minimum of computing time. The second weakness is that not all the discrimination vectors are useful in pattern classification. In this paper, we propose an uncorrelated Fisherface approach (UFA) to improve the Fisherface method in these two areas. Experimental results on different image databases demonstrate that UFA outperforms the Fisherface method and the uncorrelated optimal discrimination vectors (UODV) method.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xiao-Yuan Jing
    • 1
  • Chen Lu
    • 1
  • David Zhang
    • 2
  1. 1.Shenzhen Graduate School of HarbinInstitute of TechnologyShenzhenChina
  2. 2.Dept. of ComputingHong Kong Polytechnic UniversityKowloon, Hong Kong

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