Face recognition using improved-LDA

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 directLDA 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. © Springer-Verlag 2004.