An Improved Optimal Set of Statistical Uncorrelated Discriminant Vectors
Wu Xiao-Jun①②③; Yang Jing-Yu④; Wang Shi-Tong④; Josef Kittler③; Lu Jie-ping①
①Dept of Computer Science Jiangsu Univ. of Sci. and Tech.,Zhenjiang 212003 China;②Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110015 China;③CVSSP Dept of Electrical Engineering University of Surrey GU27XH,UK;④School of Information Nanjing University of Science & Technology Nanjing 210094 China
Abstract：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.
吴小俊; 杨静宇; 王士同; Josef Kittler; 陆介平. 改进的统计不相关最优鉴别矢量集[J]. 电子与信息学报, 2005, 27(1): 47-50 .
Wu Xiao-Jun①②③; Yang Jing-Yu④; Wang Shi-Tong④; Josef Kittler③; Lu Jie-ping①. An Improved Optimal Set of Statistical Uncorrelated Discriminant Vectors. , 2005, 27(1): 47-50 .
2005, Vol. 27 
