A NEW APPROACH TO FACE RECOGNITION BY USING DECIMATION ALGORITHM AND PCA

摘要

This paper proposes a new approach to face recognition that provides dual dimension reduction making the system computationally efficient with better recognition results as compared to traditional PCA. In all pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Then PCA is applied on the preprocessed decimated images and eigenvectors against highest eigenvalues corresponding to number of subjects used are retained. Preprocessing of the image is carried out to increase its robustness against variations in poses, light conditions and illumination level. The proposed model was tested on ORL database. The results are much encouraging as compared to standard PCA technique.