A New Method for Face Recognition Based on PCA Optimize Strategy

摘要：

This paper is focused on the problem of selecting optimum discrimination eigenvectors of PCA and improving the recognition accuracy. A new method for face recognition based on PCA optimize strategy is presented, in which the PSO algorithm is embedded, which select the recognition accuracy as the fitness value of particle swarm, to find out the optimum discrimination eigenvectors of PCA and obtain the optimal recognition accuracy simultaneously. We validate the effectiveness of this method with the ORL database and the Yale database. The experimental results indicate that the method can obtain the optimum discrimination eigenvector of PCA and a major improvement on recognition accuracy compared with the eigenvector selection approach based on the energy accumulative contribution rate.

关键词： principal component analysis face recognition particle swarm optimization

作者: Jian Zhang Xianyun Fei Yong Zhang

作者单位: Huaihai Institute of Technology Lianyungang, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 417-420

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）