Detecting and locating human eyes in segmented facial images

This paper presents a novel algorithm for automatic localization of human eyes in grayscale still images with complex background based on geometrical facial features and image segmentation, First of all, a determination criterion of eye location is established by the priori knowledge of geometrical facial features. Secondly, a range of threshold values that would separate eye blocks from others in a segmented facial image is estimated from the facial image histogram. Thirdly, with the progressive increase of the threshold by an appropriate step in that range, the size of the existing blocks in the segmented facial image will expand, some existing blocks will merge into one block, and some. new blocks will emerge. Once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. In this way, the optimal threshold value can be automatically found based on the result of detection such that eyes can be accurately located. The experimental results demonstrate the high efficiency of the algorithm in runtime and correct localization rate.