Normalized Direct Linear Discriminant Analysis with Its Application to Face Recognition

摘要

PCA plus LDA (FDA) and Direct LDA (DLDA) are two popular methods to solve the SSS problem of LDA. In this paper, we point out the relationship of these two methods and discuss the deficiency of DLDA. Then a normalized direct linear discriminant analysis (NDLDA) method which overcomes the deficiency of DLDA is proposed. Experiments on YALE face database show the superiority of NDLDA over DLDA and FDA.