Image analysis method for ocular movement measurement

For the avian vision study in behavioral experiments, an image analysis method is developed in order to measure the ocular movement of Aves based upon captured images from common CCD cameras. Firstly, genetic algorithm (GA) based multi-level gray clustering is used to segment the original image, and region growing is used to label the consecutive areas so as to rudely locate the pupil region. Secondly, the holes in pupil caused by cornea reflection are eliminated according to the approximate circinal geometric property of the pupil. Finally, the edge of the pupil is detected using the mean and standard deviation of the histogram of the edge pixels to correct the profile of pupil, and then the center of gravity is calculated to determine the pupil center. The proposed method is applied to the visible-light image and IR-illuminated image in the experimental condition, and contrasted with a method based on active contour. The results show excellent performance in the respect of less dependence on the prior knowledge of eye features, the robustness for noise and the precise location of the pupil.