Abstract: As the face image always has a blur boundary and little gradient change,the region segmentations obtained by the original active contour model are generally unsatisfactory.To achieve more accurate facial contour extraction and face segmentation,a new face segmentation scheme based on curve evolution modelis proposed,which is a combination of face detection,active contour model and mathematical morphology operators.Moreover,an improved active contour model isproposed to increase the accuracy of face contour extraction and speed up the convergence process.Experimental results show that the improved active contour model can effectively detect the local blur and breaking boundaries without any fractures in the curve,resulting in a favorable face segmentation.In addition,the improved narrow-band method reduces the computation by 60%.

Key words: face segmentation, geodesic active contour model, chan-vese model, level set method