A typical iris recognition system includes iris imaging, iris location, iris recognition and pattern matching.
虹膜识别系统主要包括了图像采集、虹膜定位、虹膜识别和模式匹配四个部分。
The paper discusses the methods of iris location and image enhancement, and proposes a phase matching algorithm to recognize and identify iris.
此文讨论了虹膜图像定位、增强等预处理的方法，并提出了一种相位相关的匹配算法对虹膜图像进行识别和判断。
Experiments show that the method has good performance for the iris location, and it avoids the effect which is brought about by the other region besides the iris.
实验结果表明，此种方法能够准确地进行虹膜内外边缘定位，避免了含有大量其它区域对定位带来的影响。
A fast iris location algorithm is proposed to aim at the problems such as inner edge deformation in iris and blurring outer edge leading to difficult iris location.
针对虹膜内边缘易变形，外边界边缘模糊从而虹膜定位困难等问题，提出了一种快速虹膜定位算法。
Owing to the difficulties in extracting iris edge image, a new iris location algorithm using geometric symmetry feature and edge detection from gray scale image is presented.
针对虹膜二值边缘图像提取的困难，提出利用虹膜图像的灰度边缘图像以及虹膜的几何特征进行虹膜定位的快速算法。
In the step of exact location, the district method is adopted in view of the iris edge gradation jump characteristic to accurately to locate the iris the outside edge.
精定位阶段针对虹膜边缘灰度跳变特性采取了分区方法准确定位虹膜的外边缘。
After finding parameter of coarse location, the inner and outer circle can be got based on the parameter because the circle of pupil and circle of iris nearly have the same center.
采用二值化的方法获得瞳孔的粗定位的参数后，由于瞳孔和虹膜的外边缘近视为同心圆，该参数可用作提取虹膜外边缘的基础。
Get an approximate iris area and an eyelash threshold in inner edge location module.
首先利用虹膜内边界定位信息，确定外边界大致区域和睫毛阈值。
Get an approximate iris area and an eyelash threshold in inner edge location module.
首先利用虹膜内边界定位信息，确定外边界大致区域和睫毛阈值。
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