An Efficient Face Recognition with ANN using Hybrid Feature Extraction Methods

Now a day’s face recognition is the most interesting and active research area in the field of phycology, neuroscience, and computer vision. In this paper a fast efficient algorithm is developed with the better recognition rate of face in different conditions that is illumination, head pose, expressions etc. In which we have extract the global and local features using PCA (Principle Component Analysis) and LBP (Local Binary Pattern) respectively. we have experiment the proposed algorithm with the standard Yale database which contains 15 individuals with each contains 11 images(15*11). So the fusion of Global and Local features are fed to the MLP (Multilayer Perceptron). The BPMLP (Backpropagation Multilayer Perceptron) is used for the classification. The proposed method achieves 93 % accuracy compare to the existing approach