In the existing LDA models, class mean vector is always estimated by the class sample
average. In small sample size problems such as face recognition, however, the class sample …

A new LDA-based face recognition system is presented in this paper. Linear discriminant
analysis (LDA) is one of the most popular linear projection techniques for feature extraction …

Abstract Linear Discriminant Analysis (LDA) is a popular feature extraction technique for
face image recognition and retrieval. However, It often suffers from the small sample size …

Linear discriminant analysis (LDA) is a popular feature extraction technique in statistical
pattern recognition. However, it often suffers from the small sample size problem when …

Linear discriminant analysis (LDA) provides the projection that discriminates data well, and
shows a good performance for face recognition. However, since LDA provides only one …

Abstract In existing Linear Discriminant Analysis (LDA) models, the class population mean is
always estimated by the class sample average. In small sample size problems, such as face …

An Improved LDA method is proposed in this paper. A weakness of Existing fuzzy LDA
model is that the class mean vector in the expression of between-class scatter matrix is …

Abstract Linear Discriminant Analysis (LDA) technique is an important and well-developed
area of image recognition and to date many linear discrimination methods have been put …

It has been demonstrated that the Linear Discriminant Analysis (LDA) approach outperforms
the Principal Component Analysis (PCA) approach in face recognition tasks. Due to the high …

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 …