Segmentation of skin color regions based on fuzzy cluster

Skin color is an important feature for face detection in color images. By building and applying a statistical skin color model, possible face regions in color images can be obtained. However, due to the inclusion of different races of people´s skin color points, this general statistical model is not accurate enough to segment each specific image as we expected. Besides, most 2D skin color models, e.g. CbCr, which is a 2D projection of 3D color distribution, cannot adapt itself to lighting variations. So, we present a 3D CrCbCg model to describe the skin color distribution more precisely. Meanwhile, considering skin points in a specific image have a relatively stable distribution, we present a fuzzy cluster based skin model to remove background points which are wrongly retained by the general model. Experimental results show that our algorithm can effectively improve segmentation results.