Face recognition for remote database backup system

Face recognition is one of the most interesting applications in the image processing field. To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features. In this research a face recognition model is developed. The dataset used is of different face images. Neural Networks technique, specifically Multilayer Perceptron (MLP) model with Back-Propagation learning algorithm and Template Matching approach are implemented in model developed. The face recognition model developed is then applied on a remote database backup system. Template matching approach is found to give a higher percentage of matching accuracy and a faster result can be obtained compared to MLP as no learning process is required.