This paper presents a novel algorithm to quickly detect faces from still gray level images. The algorithm first detects the upper eyelid pixels using the eye region's gray and gradient information, which can be computed by the integral image very quickly. Then according to the anthropological characteristic of human face, some rules are used to select eyes and the pairs of eyes candidates from the detected eyelid pixels. Finally, a hierarchy method is proposed to verify whether a pair of eyes candidate corresponds to a true face. Experiment on the BioID face database shows that the proposed method is very robust to detect the upper eyelid pixels and the rate of face detection is satisfactory. In terms of accuracy of eye detection, the proposed method outperforms other methods.
This paper presents a new method for locating eye accurately. In the first stage, the proposed method finds the coarse eye region from image using genetic algorithm based on the edge information and intensity distribution information. In the second stage, ellipse detection is employed to extract the boundary of the iris. The experimental results have shown that the proposed method can locate eyes accurately from the input image with complex background.