Lip segmentation by fuzzy clustering incorporating with shape function

In lip segmentation, most of the clustering methods are based on color information. In this paper, a new fuzzy clustering method that combines the color information and the shape information in the measure is proposed. An elliptic shape function is introduced in the measure that modifies the measure according to the distance of the pixel from the lip center with which the differentiation between the lip and non-lip regions is enhanced. Compared with the standard fuzzy c-means algorithm, experimental results show that the new algorithm has better membership distribution and shape. This method is applicable to other images with a well-predicted shape.