A New Hybrid Approach Using PCA for Pose Invariant Face Recognition

摘要

In this paper a new hybrid approach using PCA for pose invariant face recognition is proposed. In this proposed approach three algorithms are combined to make a new hybrid approach. The first step is to detect face and its part. It is done by well known Viola Jones algorithm. In this proposed new hybrid approach using PCA, five parts of face image are detected and these are face, left eye, right eye, nose and mouth. The second step is to find local binary pattern (LBP) of each part. LBP extracts features from the detected faces and its parts. The third step is to apply PCA on each extracted feature for recognition. It is seen from the experimental results that proposed hybrid approach using PCA gives improved recognition rate for face images with different facial expression and poses. It is when compared with conventional PCA, PCA+ Wavelet, 2DPCA, 2DPCA + DWT and LBP algorithms shows improved recognition rate for face images. The accuracy of the conventional PCA and hybrid approach using PCA are evaluated under the conditions of varying expression and pose. The images are taken from ORL face databases.