This paper describes a fully automated technique of detecting lip contours from static face images. Face detection is performed first on the input image using a variation of the AdaBoost classifier trained with Haarlike features extracted from the face. A second trained classifier is applied over this extracted face region for isolating the mouth section. The detection of lip contour is then performed from this isolated mouth region using the level set method of image segmentation. A new variational formulation of level set method, proposed by Li et al. (CVPR-2005), has been applied here that forces the level set function to be close to a signed distance function and therefore completely eliminates the need of the costly reinitialization procedure. The proposed method has been tested on three different face databases that contain images of both neutral faces as well as facial expressions, and a maximum successful lip contour detection rate of 91.08% has been achieved.