一种利用分块统计的虹膜定位算法

虹膜识别是一种新兴的生物特征识别技术，而虹膜定位是虹膜识别的重要步骤，因而精确而快速地进行虹膜定位是有效地进行虹膜识别的重要前提。为了能够快速地进行虹膜定位，在简要介绍现有的虹膜定位算法的基础上，提出了一种新的利用分块统计的虹膜定位算法。由于虹膜边缘可以简单地用圆周描述，因此，该算法第1步先阈值化分割图像，以分别建立虹膜和瞳孔的二进制位图；第2步用游长编码的方法来寻找最大色块的质心，并计算边界点到质心距离的均值。实验结果表明，对于虹膜定位而言，该算法是实用而且有效的。

An Algorithm for Iris Localization Using Block Statistic

Iris recognition is an emerging biometric technology for personal identification, whereas iris localization is a crucial part in the process of iris recognition,thus obtaining the iris localization precisely and fleetly is the prelude of effective iris localization . For the purpose of localizing iris precisely, this paper puts forward a novel algorithm of iris localization using block statistic while based on introducing some prevailing algorithms for iris localization. The boundaries that delimit iris can be modeled in a simple way with circular contours. Therefore ,the first step in the paper consists of thresholding the iris image intensity to build two binary bitmaps for the succeeding image procession, one for the whole iris and the other for the pupil. The second step is to search for the centroid of the largest block in the iris binary bitmaps by means of Run Length Encoding (RLE), and calculate the average distance from each point of the boundaries to the centroid obtained before. Experiments show that the algorithm is efficient and successful for the purpose of iris localizing.