Face Detection In Color Images

Human skin color has been proven to be an effective feature and widely used in face detection in resent years. However, color is not a physical phenomenon. It is a perceptual phenomenon that is related to the spectral characteristics of electromagnetic radiation in the visible wavelengths striking the retina. How to improve the performance of the skin detector is a challenging problem.Neural Networks are parameterized non-linear models used for empirical regression and classification modeling. Their flexibility makes them able to discover more general relationships in data than traditional statistical models.Firstly an improved GAs is proposed and shows better performance in comparison with SGA and AGA. Secondly the traditional statistical skin models are studied and a novel approach to design a neural network based skin detector is put forward, which will be later used to retrieve skin-like pixels in color face images. Further more, an evolutionary search procedure (GAs) also has been introduced into the neural network training process. The experiment shows that the evolutionary neural network based skin detector performs much better than traditional skin color models.At last, we applied both the improved GAs and the skin detector to the face detection, and got impressive results. The eyes can be considered as a salient andrelatively stable feature of faces, so firstly eyes-analogue regions in cluttered images are segmented using local adaptive threshold edge detector. Then the small eye-analogue regions are grouped together and labeled using a traditional labeling process according to their geometrical and color features. Instead of finding potential eye-pairs from eye-analogue regions one by one, all possible pairs of eyes are encode as the solution, and the potential face are searched by GAs. In this way, the possible solution space is reduced dramatically. The evaluate function is defined by the combination of horizontal gray projection and skin color in the regions of eyes and cheek.