Eye detection based on grayscale morphology
Hai Ying Han, T. Kawaguchi, Ryoichi Nagata · 2004
In this paper we propose a new algorithm to detect eyes in intensity images. The algorithm can detect eyes directly from the whole image. In the algorithm, eyes and mouth are modeled by upright ellipses and cheeks are modeled by circles. The algorithm first detects a valley map of the intensity image using grayscale morphology. In the valley map, eyes and mouth have many valley pixels while cheeks have few valley pixels. In addition, the movement of eyes and mouth decreases valley pixels inside them while the movement of cheeks increases valley pixels inside them. Using these properties of facial features, the algorithm detects two circles corresponding to cheeks and three ellipses corresponding to eyes and mouth. As the results of the experiments using 252 faces without spectacles in the AR face database show, the eye detection rate of the proposed algorithm was 98.8%.