Region based fuzzy neural networks for face detection

In this paper, we propose a fuzzy neural network method for face detection. In the proposed method, fuzzy membership degrees are assigned to preprocessed 20x20 window face and non-face image regions. These fuzzy membership degrees are then inputed to a neural network to be trained using the error back propagation training method. After training, the output value of the neural network is interpreted as the degree of which a given window is a face or non-face region. If the window is determined to contain a face, post processing is then performed. Experimental results show that the proposed method can detect face images more accurately than using conventional neural networks. Also, the proposed fuzzy neural network architecture is shown to require less number of hidden neurons than when using conventional neural networks.