Lip segmentation in color images

Lip feature extraction is one of the most challenging tasks in the lip reading systems´ performance. In this paper, a new approach for lip contour extraction based on fuzzy clustering is proposed. The algorithm employs a stochastic cost function to partition a color image into lip and non-lip regions such that the joint probability of the two regions is maximized. First, the mouth location is determined and then, lip region is preprocessed using pseudo hue transformation. Fuzzy c-means clustering is applied to each transformed image along with b components of CIELAB color space. To delete the clustered pixels around lip, an ellipse and a Gaussian mask were used. In order to show the performance of the proposed method, the pseudo hue segmentation and fuzzy c-mean clustering without preprocessing are compared. The compared methods were applied to the VidTIMIT and M2VTS databases and the results show the superiority of the proposed method in comparison with other methods.