An analytical algorithm for determining the generalized optimal set of discriminant vectors

Generalized linear discriminant analysis has been successfully used as a dimensionality reduction technique in many classification tasks. An analytical method for finding the optimal set of generalized discriminant vectors is proposed in this paper. Compared with other methods, the proposed method has the advantage of requiring less computational time and achieving higher recognition rates. The results of experiments conducted on the Olivetti Research Lab facial database show the effectiveness of the proposed method.