Astute, fine and fast method of iris segmentation in unlimited circumstances

Currently, Iris detection is considered as a significant module for robust biometric systems and high-speed applications such as eye tracking. Most iris segmentation models are based on machine learning algorithms or geometric methods. In this paper, we use an elliptical Hough transform to firstly detect the shape of the palpebral fissure. Then, a correlation-based circular Hough transform (we named it CCHT) is proposed to extract iris from the surrounding structures. One of the advantages of the proposed method is its ability to determine the closed-eye images, in order to remove these images in the process of eye tracking procedure. Moreover, the algorithm is simple and fast which make it suitable for on-line eye tracking. Experimental results on UBIRIS, which contains some defocused and eyelid-occluded images as non-ideal and noisy frames, indicate that the proposed method is efficient and much faster, in comparison with the previous approaches and encouraging improved accuracy on iris detection.