A Co-evolutionary Approach toward Face Localization in Color Images

In this paper a new method for face localization in color images, which is based on co-evolutionary systems, is introduced. The proposed method uses a co-evolutionary system to locate the eves in a face image. The used co-evolutionary system involves two genetic algorithm models. The first CA model searches for a solution in the given environment, and the second GA model searches for useful genetic information in the first GA model. In the next step, by using the location of eyes in image the parameters of face's bounding ellipse (center, orientation, major and minor axis) are computed. To evaluate and compare the proposed method with other methods, high order Pseudo Zernike Moments (PZM) are utilized to produce feature vectors and a Radial Basis Function (RBF) neural network is used as the classifier. Simulation results indicate that the speed and accuracy. of the new, system using the proposed face localization method which uses a co-evolutionary approach is higher than our previous system [10].