Occluded face recognition based on Gabor wavelets

A new feature based approach to frontal face recognition with Gabor wavelets is presented. The feature points are automatically extracted using the local characteristics of each individual face in order to decrease the effect of occluded features. There is no training as in neural network approaches, thus a single frontal face for each individual is enough as a reference. Experimental results show that the proposed method achieves a recognition ratio of over %95.