虹膜定位是虹膜识别中非常重要的一个环节。
Iris localization is a very important part of iris recognition.
提出了一种基于图像抽样的快速虹膜定位算法。
A rapid iris localization algorithm based on image sampling was proposed.
虹膜定位以及质量评估是虹膜识别系统中的关键步骤。
In the system of iris recognition, iris localization and iris image quality assessment are very critical.
实验结果证明改进的CRHT算法提高了虹膜定位速度。
Experiments show that the improved CRHT algorithms gained higher speed.
在虹膜定位方面，提出一种基于人眼结构特征的定位方法。
In iris localization, a method of iris localization based on the human eye structure is presented.
目前主流的虹膜定位算法在速度上都不能满足虹膜识别系统的实时要求。
Most accurate iris locating algorithm can't satisfy the time requirement of iris recognition system.
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。
A typical iris recognition system includes iris imaging, iris location, iris recognition and pattern matching.
虹膜识别系统一般可由虹膜定位、图像预处理、虹膜特征提取和分类识别几个部分组成。
Iris recognition system is made up by iris localization component, iris image preprocessing, iris feature extraction and classification.
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。
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。
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.
虹膜图像的预处理主要分为四步：内外边缘定位、图像归一化、图像增强和有效区域的划分。
Iris image preprocessing includes four parts: iris localization, iris normalization, iris image enhancement and choice of the valid region.
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。
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.
实验结果表明此方法算法简单、计算量小、抗干扰性强，并且能够准确的定位虹膜的内边缘。
Experiment results show that the proposed method is simple, requires minor calculations, exhibits a strong ability to reject noise, and is accurate in locating the iris inner boundary.
虹膜边界定位精度和定位速度影响识别系统性能。
The accuracy and the speed of iris boundary localization affect recognition system performance.
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。
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.
因此，必须在提高定位速度的同时保持定位的精度，不使虹膜纹理信息丢失。
So when improving the speed and accuracy of iris localization, we must try our best not to lose iris texture information.
快速、准确地定位虹膜是虹膜识别系统的关键。
The speed and accuracy of iris localization is crucial in an iris recognition system.
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。
The paper discusses the methods of iris location and image enhancement, and proposes a phase matching algorithm to recognize and identify iris.
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。
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.
由于在经过定位预处理之后的原始虹膜图像中，存在可能干扰定位的多种因素。
This paper particularly analyzes some factors possibly disturbing iris localization in the iris image through the localizing pre processing.
最后对定位后的虹膜图像进行了归一化。
虹膜图像的预处理包括虹膜图像的定位、归一化、增强和去噪。
It is composed of iris localization, iris normalization, iris image enhancement and denoising in image preprocessing.
本文主要讨论了对虹膜采集装置的改进、定位、图像质量评定、活体检测和编码以及测试统计。
The researches are mainly focused on the improvement of iris sampling equipment, iris localization, the quality evaluation of iris image, live detection, coding and test statistic.
虹膜在图像中的位置和大小不固定，这使得虹膜边界定位计算量大，定位速度慢。
Because the position and the size of irises in images are not fixed, these reasons result in that the computing burden increases and the iris boundary localization is slow.
提出了一种基于彩色分割的虹膜检测方法，对于一幅经过准确定位的眼睛窗口图像，它的彩色信息比灰度信息更有助于进行虹膜检测。
This paper proposes an iris detection method based on color segmentation. To a localized eye image, color images contain more information helpful for detecting irises than intensity images.
本方法主要针对定位容易出现错误的外边界，利用虹膜的结构特征和数学手段，对得到的虹膜外边界点进行验证，必要时通过计算得到准确的外边界点。
To the iris' outer boundary, we use the feature of the iris' structure and mathematical means to verify whether the iris outer boundary points are correct, and calculate the correct ones if necessary.
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.
预处理过程中对虹膜的精确定位，使定位后的虹膜图像具有平移、尺度和旋转的不变性。
Precision locating for iris in the process of preprocessing makes iris image have invariance in translation, size and rotation.
预处理过程中对虹膜的精确定位，使定位后的虹膜图像具有平移、尺度和旋转的不变性。
Precision locating for iris in the process of preprocessing makes iris image have invariance in translation, size and rotation.
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