A New Pupil Detection Algorithm Based on Circular Hough Transform Approaches

In this paper a new pupil detection algorithm based on circular Hough transform approaches is presented. The proposed algorithm includes an adaptive quantitative binarization procedure, a pupil reconstruction stage by using certain morphological operations and the image contour detection performed with the Laplace operator. To save the computing resources, the circular Hough transform is applied on the edge of the binarized eye image and provides better results for noisy eye image captured in nonuniform and variable lighting conditions. The CHT based algorithm achieves a detection rate at five pixels higher than 82% for three different and highly representative databases, totalizing 1324 eye images.