Modelling and segmentation of lip area in face images

Abstract

The problem of automatic segmentation of face images to extract the lip area is considered in the context of lip tracking. A novel segmentation method is proposed for lip tracker initialisation which is based on a Gaussian mixture model of the pixel RGB values. The model is built using the predictive validation technique advocated by Kittler which has been modified to allow modelling with full, rather than just diagonal covariance matrices. A subsequent grouping of the mixture components provides the basis for a Bayesian rule labelling of the pixels as lip or non-lip. The proposed method is tested on a database of 145 images and demonstrates that its accuracy is significantly better than the segmentation obtained by k-means clustering. Moreover, the proposed method does not require the number of segments to be specified a priori.