Automatic face recognition system using neural networks

Automatic recognition of individuals is a significant problem in the development of pattern recognition. In this paper, we introduce a simple technique for personal identification through human faces in cluttered scenes based on neural nets. In the detection phase, neural nets are used to test whether a window of 20/spl times/20 pixels contains a face or not. A major difficulty in learning process comes from the large database required for face/nonface images. We solve this problem by dividing these data into two groups. Such division results in a reduction of computational complexity and thus decreasing the time and memory needed during the test of an image. For the recognition phase, feature measurements are made through Fourier descriptors. Such a feature is modified to reduce the number of neurons in the hidden layer. Simulation results for the proposed algorithm show a good performance compared with previous results.