Face Recognition by Using Neural Network Classifiers Based on PCA and LDA
Byung-Joo Oh · 2006
This paper proposes a face recognition method using neural network classifiers based on principal component analysis (PCA) and linear discriminant analysis (LDA). The PCA or LDA features of the face images are then classified by the multiple layer neural network (MLNN) or radial basis function (RBF) network. The proposed approach has been tested on the ORL database. The experimental results have been demonstrated that the performance of PCA+MLNN is superior to that of the LDA+RBFN.