基于角积分投影和活动轮廓模型的精确瞳孔边界检测

Ann A. Jarjes Alkazzaz, Kuanquan Wang, Ghassan J. Mohammed Aladool
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引用次数: 1

摘要

在基于虹膜的生物识别应用中,精确的瞳孔轮廓检测对虹膜定位具有重要意义。提出了一种检测虹膜图像中精确瞳孔轮廓的新算法。该算法检测精确的瞳孔轮廓,而不是将瞳孔边界视为一个完美的圆,这降低了后续虹膜匹配的性能。它包括两个检测阶段,第一阶段检测圆形瞳孔轮廓,第二阶段检测精确瞳孔轮廓。首先确定近似瞳孔中心作为二值化虹膜图像的质心,然后应用角积分投影函数(AIPF)检测一组瞳孔边界点,最后在检测到的边界点上拟合圆得到瞳孔圆形轮廓。在第二阶段,采用基于贪婪优化算法的活动轮廓模型,在第一阶段得到的瞳孔圆上初始化,从而检测出准确的瞳孔轮廓。在三种不同的虹膜数据库上的实验结果表明,与现有的虹膜分割方法相比,该算法可以在更短的执行时间内准确地检测出瞳孔轮廓,验证了算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precise Pupil Boundary Detection Using Angular Integral Projection and Active Contour Model
Precise pupil contour detection is of great importance to iris localization in iris-based biometric applications. A new algorithm for detecting the precise pupil contour in iris images is presented in this paper. The proposed algorithm detects the exact pupil contour rather than considering pupil boundary as a perfect circle which degrades the performance of later iris matching. It comprises two detection phases, the first for circular pupil contour and the second for the exact pupil contour. In the first phase, the approximate pupil center is determined as the center of mass of the binarized iris image, then the angular integral projection function (AIPF) is applied to detect a set of pupil boundary points, and finally the pupil circular contour is obtained by fitting a circle to the detected boundary points. While in the second phase, the accurate pupil contour is detected by employing an active contour model which is based on greedy optimization algorithm that is initialized on the pupil circle obtained form the first phase. Experimental results on three different iris databases indicate that the proposed algorithm can accurately detect pupil contour in less execution time as compared with other existing methods for iris segmentation, which confirms its performance.
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