An uncorrelated fisherface approach for face and palmprint recognition

Authors:
Xiao-Yuan Jing;Chen Lu;David Zhang
Affiliations:
Shenzhen Graduate School of Harbin, Institute of Technology, Shenzhen, China;Shenzhen Graduate School of Harbin, Institute of Technology, Shenzhen, China;Dept. of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

Citing 2
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Abstract

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.