Gabor-Based Improved Locality Preserving Projections for Face Recognition

A novel Gabor-based improved locality preserving projections for face recognition is presented in this paper. This new algorithm is based on a combination of Gabor wavelets representation of face images and improved locality preserving projections for face recognition and it is robust to changes in illumination and facial expressions and poses. In this paper, Gabor filter is first designed to extract the features from the whole face images, and then a locality preserving projections, which is improved by two-directional 2DPCA to eliminate redundancy among Gabor features, is used to subject these feature vectors onto locality subspace projection. Experiments based on the ORL face database demonstrate the effectiveness and efficiency of the new method. Results show that our new algorithm outperforms the other popular approaches reported in the literature and achieves a much higher accurate recognition rate.