2-D Discriminative Component Analysis for Face Recognition

Principle component analysis(PCA) and linear discriminant analysis(LDA) are known as classical techniques used in face recognition. Both 2-D PCA, 2-D LDA are based on 2-D matrices as opposed to classical PCA and LDA which are based on 1-D vectors. In current work discriminative component analysis(DCA) simultaneous projection of probe image into PCA and LDA face spaces for face recognition is proposed. Also Alternate DCA is proposed. The study is conducted on AT&T database (formerly ORL database) and study reports are encouraging as that of other analysis.