应用迭代圆环像素率法实现快速虹膜定位

针对虹膜定位易受噪声影响、速度慢、自适应性差等问题,提出了基于迭代圆环像素率法的快速虹膜定位算法。提出的定位算法包括切割虹膜图像、Hough圆检测粗定位、微积分算子精定位3个部分,从切割虹膜图像、图像抽样、迭代圆环像素率法、快速Hough圆检测以及分层定位思想5方面提高算法的速度。提出了缩小半径范围的迭代圆环像素率法以及消除瞳孔光斑的形态学方法,瞳孔分割阈值以及小范围的圆心、半径候选集等参数都是通过计算得到,自适应性好。使用4个虹膜数据库进行实验,并与相近算法进行了对比。实验结果表明,该算法的定位准确率为97.75%～99.07%,定位时间为52.847～158.502 ms,是一种鲁棒、快速、自适应的虹膜定位算法。

Rapid iris localization based on method of iterative pixel ratio to cirque area

Aimed at the problems of noise influence, high time consumption and bad adaptive performance for iris localization, a rapid iris localization algorithm based on the method of iterative pixel ratio to cirque area is proposed. The proposed method is composed of 3 parts: cutting iris image, coarse localization by circle detection of the Hough transformation and the precise localization by an integrodifferential operator. The methods of cutting the iris image, image sampling, iterative pixel ratio to cirque area, rapid circle detection of the Hough transformation and the layered localization theory are used to improve the algorithm speed. The method of iterative pixel ratio to cirque area is put forward to reduce the radius range, and the morphological method is used to eliminate the pupil faculae. The threshold of pupil segmentation,small-range candidates of circle centre and radius, etc. are all obtained by the computation with good adaptive performance. Finally,four iris databases are applied in the experiments, and experimental results are compared with other algorithms. The results show that the accuracy of the proposed algorithm is 97.75%~99.07% and the time consumption is 52.847~158.502 ms. The experiments prove that the proposed method is a robust, rapid, adaptive iris localization algorithm with good comprehensive performance.