Locating and extracting the eye in human face images

Facial feature extraction is an important step in automated visual interpretation and human face recognition. Among the facial features, the eye plays the most important part in the recognition process. The deformable template can be used in extracting the eye boundaries. However, the weaknesses of the deformable template are that the processing time is lengthy and that its success relies on the initial position of the template. In this paper, the head boundary is first located in a head-and-shoulders image. The approximate positions of the eyes are estimated by means of average anthropometric measures. Corners, the salient features of the eyes, are detected and used to set the initial parameters of the eye templates. The corner detection scheme introduced in this paper can provide accurate information about the corners. Based on the corner positions, we can accurately locate the templates in relation to the eye images and greatly reduce the processing time for the templates. The performance of the deformable template is assessed with and without using the information on corner positions. Experiments show that a saving in execution time of about 40% on average and a better eye boundary representation can be achieved by using the corner information.