Locatization of human eyes based on a series of binary images
A new method for eyes localization is presented. By incorporating some eye geometrical constraints, our method includes such procedures as eyes image segmentation, eye candidates selection and eyeball detection. In order to locate the eyes more precisely, the valley map transformed from the grayscale face image using an arithmetical morphology method is successively binarized with a series of threshold values determined adaptively, and many possible eyeball candidates are extracted from them. The final position of the two eyes is obtained using a statistical method. Experimental results on AR and Yale face databases show that a locating rate of over 94% and an average locating disparity of below 2 pixels can be achieved