A Novel Fisher Criterion Based St-Subspace Linear Discriminant Method for Face Recognition.

In this paper, a novel Fisher criterion is introduced and shown to be equivalent to the traditional Fisher criterion. Based on this new Fisher criterion and simultaneous diagonalization technique, a St-subspace Fisher discriminant (St-SFD) method is developed to deal with the small sample size (S3) problem in face recognition. The proposed method overcomes some drawbacks of existing LDA based algorithms. Also, our method has good computational complexity. Two public available databases, namely ORL and FERET databases, are exploited to evaluate the proposed algorithm. Comparing with existing LDA-based methods in solving the S3 problem, the proposed St-SFD method gives the best performance. [ABSTRACT FROM AUTHOR]