Automatic extraction of head and face boundaries and facial features

This paper presents a novel approach for the extraction of human head, face and facial features. In the double-threshold method, the high-thresholded image is used to trace head boundary and the low-thresholded image is used to scan face boundary. We obtain facial features candidates and eliminate noises, and apply x- and y-projections to extract facial features such as eyes, nostrils and mouth. Because low contrast of chin occurs in some face images, its boundary cannot be completely detected. An elliptic model is used to repair it. Because of noises or clustered facial features candidates, we apply a geometric face model to locate facial features and an elliptic model to trace face boundary. The Gabor filter algorithm is adopted to locate two eyes. We have tested our algorithm on more than 100 FERET face images. Experimental results show that our algorithm can perform the extraction of human head, face and facial features successfully.