Abstract
Design a fast and reliable iris segmentation algorithm for less constrained iris images is essential to build a robust iris recognition system. Daugman's integrodifferential operator (IDO) is one of powerful iris segmentation mechanisms, but in contrast consumes a large portion of the computational time for localising the rough position of the iris centre and eyelid boundaries. To address this problem, a fast iris segmentation algorithm is proposed. First, the circular Gabor filter is adopted to find the rough position of the pupil centre. Second, the iris and pupil circles are localised using the IDO taken into account that the real centres of the iris and pupil are in the small area around the rough position of the pupil centre. Third, the upper and lower eyelid boundaries are extracted using the live-wire technique. Experimental results demonstrate that the proposed iris segmentation algorithm significantly minimises the required time to segment the iris without affecting the segmentation accuracy. Moreover, the comparison results with state-of-the-art iris segmentation algorithms show the superiority of the proposed algorithm in terms of segmentation accuracy and recognition performance. The challenging UBIRIS.v1 iris image database is utilised to evaluate the performance of the proposed algorithm.
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