An Improved LDA Algorithm and Its Application to Face Recognition

J4 ›› 2011, Vol. 33 ›› Issue (7): 89-91.

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An Improved LDA Algorithm and Its Application to Face Recognition

LIU Zhongbao

(1.School of Information Engineering,Jiangnan Univerisity,Wuxi 214122;
2.Department of Information Engineering,School of Business,Shanxi University,Taiyuan 030031,China）

Received:2010-07-20 Revised:2010-11-18 Online:2011-07-21 Published:2011-07-25

Abstract

Abstract:

Linear discriminant analysis (LDA) is a typical feature extraction method, but there exist at least two critical drawbacks in LDA: the small sample size problem and the rank limitation problem. In order to solve the above problems, this paper presents an improved LDA method (ILDA) which redefines the betweenclass scatter matrix and the withinclass scatter matrix. ILDA can effectively extract the discriminative information included in the null subspace and the nonnull subspace of a withinclass scatter matrix. Numerical experiments on some facial databases show ILDA achieves good performance of face recognition.

Key words: linear discriminant analysis(LDA);withinclass scatter matrix;betweenclass scatter matrix;face recognition

LIU Zhongbao. An Improved LDA Algorithm and Its Application to Face Recognition[J]. J4, 2011, 33(7): 89-91.

An Improved LDA Algorithm and Its Application to Face Recognition

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