A design of face detection system using evolutionary computation
We propose a new method to examine whether or not human faces are included in color images by using a lip detection neural network (LDNN) and a skin distinction neural network (SDNN). In conventional methods, if there are the same color as the skin color in scenes, the domain which is accepted as not only the skin color but any other color can be searched. However, first, the lip are detected by LDNN in the proposed method. Next, SDNN is utilized to distinguish the skin color from the others. The proposed method can obtain relatively high recognition accuracy, since it have the double recognition structure of LDNN and SDNN. Furthermore, in order to reduce the amount of calculation and to discriminate a skin color and the other colors, GA can search to minimize the number of necessary data. Then a storage capacity and the amount of operations can be cut down by using GA and LDNN and SDNN are trained by using the reduced data. Finally, in order to demonstrate the effectiveness of the proposed scheme, computer simulations were performed. First, 100 lip color, 100 skin color and 100 background pictures, which are changed into 10/spl times/10 pixels, are prepared for training. The validity was verified by testing images containing several faces.