A New Algorithm for Generalized Optimal Discriminant Vectors

• 作 者: 吴小俊 杨静宇 王士同 郭跃飞 曹奇英
• 机 构: East China Shipbuilding Institute, Zhenjiang 212003, P.R. China;School of Information, Nanjing Unive
• 出 处: 计算机科学技术学报(英文版)
• 发表日期: 2002年3期
• 关键词: pattern recognition feature extraction discriminant analysis generalized optimal

A study has been conducted on the algorithm of solving generalized optimal set of discriminant vectors in this paper. This paper proposes an analytical algorithm of solving generalized optimal set of discriminant vectors theoretically for the first time. A lot of computation time can be saved because all the generalized optimal sets of discriminant vectors can be obtained simultaneously with the proposed algorithm, while it needs no iterative operations. The proposed algorithm can yield a much higher recognition rate. Furthermore,the proposed algorithm overcomes the shortcomings of conventional human face recognition algorithms which were effective for small sample size problems only. These statements are supported by the numerical simulation experiments on facial database of ORL.