Face Recognition with Facial Mask Application and Neural Networks

Face recognition represents one of the most interesting modalities of biometric. Due to his low intrusiveness and to the constant decrease in image acquisition cost, it's particularly suitable for a wide number of real time applications. In this paper we propose a very fast image pre-processing by the introduction of a linearly shaded elliptical mask centered over the faces. Used in association with DCT, for features extraction, and MPL and RBF Neural Networks, for classification, it allows an improvement of system performances without modifying the global computation weight and also a learning time reduction for MLP neural networks.