Fast iris localization algorithm on noisy images based on conformal geometric algebra

Abstract In practical iris applications, the obtained iris images are inevitably affected by noises brought by uneven illumination, off-angle view, eyelids, and eyelashes etc. Such influences can lead to poor accuracy and low efficiency of iris localization. This paper presents a novel conformal geometric algebra (CGA) based algorithm for accurate and fast iris localization. Firstly, two thresholds are obtained adaptively to convert the gray image into three-value image and Sobel edge detector is used to generate the edge points. Then an improved CGA-based circle detection algorithm is applied to detect the limbic and pupillary boundaries of the iris. Candidate boundaries are found with a priori knowledge of the eye structure. Finally, the CGA inner product is used to decide whether an edge point from candidate boundaries is on the circle or not. A defect ratio is defined to represent the completeness of each candidate boundary, and only those with the lowest defect ratio are set as the pupillary and limbic boundaries. Our algorithm detects candidate boundaries that satisfy a priori constraints rapidly and ensures the accuracy of iris localization. Experimental results on different datasets demonstrate the effectiveness and robustness of the algorithm.