Face contour extraction is important in facial feature extraction and in model-based coding. For the face boundary

classical edge detection techniques will fail to exploit the inherent continuity of face boundaries. As the shape of face boundary is not uniform and exhibit low overall curvature

geometric active contours are an attractive choice for the extraction of face boundaries

but the original geometric active contour model still has no way to characterize the global face shape. In this paper a new method that incorporates prior shape information into geometric active contours for face contour extraction is proposed. As in general a human face can be treated as an ellipse with a little shape variation

the prior face shape is represented as an elliptical curve. By combining the prior face shape with the geometric active model proposed by Chan and Vese

our improved geometric active contour model can capture face contour depending on both the image edges and the prior knowledge of face shape. Moreover

our model is implemented using variational level set approach

thus the transformation parameters (such as the rotation angle in plane) that maps the face boundary to the prior shape can be roughly estimated simultaneously. The experimental results show the efficiency and effectiveness of our method.