An Improved Optimal Set of Statistical Uncorrelated Discriminant Vectors
改进的统计不相关最优鉴别矢量集

This paper presents a research on the algorithm of optimal set of statistically uncorrelated discriminant vectors. An improved algorithm has been proposed on the basis of the analysis of the conventional algorithm of statistical uncorrelated discriminant vectors, which solves the optimal set of statistically uncorrelated discriminant vectors in the eigen space of the within-class scatter matrix Sw . The dimension of images has been reduced using the dimension reduction method based on image discriminant analysis in order to speed the process of feature extraction. The numerical experiments on facial databases of ORL and Yale show the effectiveness of the proposed method.