An Improved Method for Facial Features Extraction in Images

When it is necessary to analyze a personpsilas face, whether it is for recognizing pathologies, emotions, or states of mind, it becomes necessary to obtain a maximum of information of the facial characteristics that especially reflect these aspects. These characteristics are principally, the mouth, eyes and eyebrows. The start of the analytic process, once the face and the facial feature to be analyzed have been divided into segments, consists in applying an algorithm to said feature for the detection of its edges. The most used edges algorithms are; SUSAN, Canny, Sobel, and Roberts, among others. These algorithms function excellently when the edges are fairly well defined, but in the case of faces in color, where the transitions are not clearly marked, and when there are many imperfections and shadings, the above mentioned algorithms generate incomplete contours in a great number of cases, leading to errors in high level analysis. This article presents a new methodology based on the Canny algorithm which allows us to obtain the edges of the mouth with much greater information than the other above mentioned algorithms, which makes it more adequate for the originally stated objective. The method has been tested detecting the outline contour of the mouth and using the databases of facial images, ldquoMMI facial expression database compiled by M. Pantic & M. F. Valstar" and "A.M. Martinez and R. Benavente. The AR face database. CVC technical report #24, June 1998".