Improved Face Recognition Method Using Genetic Principal Component Analysis

摘要

An improved face recognition method is proposed based on principal component analysis（PCA） compounded with genetic algorithm（GA）,named as genetic based principal component analysis（GPCA）.Initially the eigenspace is created with eigenvalues and eigenvectors.From this space,the eigenfaces are constructed,and the most relevant eigenfaces have been selected using GPCA.With these eigenfaces,the input images are classified based on Euclidian distance.The proposed method was tested on ORL（Olivetti Research Labs） face database.Experimental results on this database demonstrate that the effectiveness of the proposed method for face recognition has less misclassification in comparison with previous methods.