Finally the localized iris image is normalized.
最后对定位后的虹膜图像进行了归一化。
The quality of iris image is the key point to affect the accuracy of iris recognition system.
虹膜图像质量是影响虹膜识别系统精度的关键。
How to find the true iris position in an iris image is a key problem to be solved in iris recognition.
如何有效地确定虹膜在图像中的位置，是虹膜识别中需要解决的关键问题之一。
In the system of iris recognition, iris localization and iris image quality assessment are very critical.
虹膜定位以及质量评估是虹膜识别系统中的关键步骤。
The unitary iris image is carried out through the transformation from Cartesian coordinates to polar coordinates.
然后采用极坐标转换对虹膜图像进行归一化。
At last, the appraisal of iris image quality on the iris recognition system is discussed in the paper.
最后，在虹膜识别系统上进行虹膜图像质量的评价工作。
It is composed of iris localization, iris normalization, iris image enhancement and denoising in image preprocessing.
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。
The system based on iris is composed of iris image acquisition, image preprocessing, feature extraction and matching.
基于虹膜的识别系统由以下几个部分构成：虹膜获取、虹膜图像预处理、虹膜图像特征提取、匹配与识别。
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。
Iris recognition system includes iris image acquiring, image preprocessing, feature extraction, coding and recognition and so on.
虹膜识别系统由虹膜图像采集、虹膜图像预处理、特征提取、编码与识别等部分构成。
Iris recognition system is made up by iris localization component, iris image preprocessing, iris feature extraction and classification.
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 image preprocessing includes four parts: iris localization, iris normalization, iris image enhancement and choice of the valid region.
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。
A new kind of iris image preprocessing algorithm was presented to ameliorate the limitation of the existing iris image preprocessing algorithm.
针对目前已有的虹膜图像预处理算法的局限性，提出了一套新型的虹膜图像预处理算法。
To overcome the deficiencies of the existing recognition algorithms, this thesis has studied the iris image preprocessing and the feature matching.
本文针对现存的虹膜识别算法中的不足之处，对虹膜识别系统中的图像预处理过程和特征匹配过程进行了深入研究。
In the last, using MATLAB software realizes the algorithm of iris recognition; experiment has performed on CASIA iris image database and has got a good effect.
最后，利用MATLAB软件实现了虹膜识别算法，并在CASIA虹膜图像数据库上进行实验，取得了良好的效果。
In order to improve the accuracy and stability of iris image classification, an iris image classification method was developed based on minimax probability machine.
为了提高虹膜图像分类的准确性和稳定性，提出了一种基于最小最大概率机的虹膜图像分类方法。
In order to ensure high recognition rate and remove the disturbing factor in iris image, an algorithm of segment detection is proposed to detect eyelid and remove it.
虹膜图像中通常包含了干扰因素的眼睑，为了消除影响识别效果的这种干扰因素，保证较高的识别率，提出一种分段检测算法。
The accordance of personal identification makes use of iris image abundant structure and streak feature, more reliable than other biometric characteristic recognition.
利用虹膜图像中丰富的结构和纹理特征作为身份鉴别的依据，与其他生物特征识别相比，具有更高的可靠性。
A personal identification system based on iris patterns is composed of iris image acquisition, image preprocessing, feature extraction and coding, matching and recognition.
基于虹膜的识别系统由以下几个部分构成：虹膜获取、虹膜图像预处理、虹膜图像特征提取、匹配与识别。
A kind of iris image acquisition system is proposed based on floating-point DSP chip TMS320VC6711. Its principle, design and realization of software and hardware are introduced.
提出了一种基于红外光源的、以浮点DSP芯片TMS320 VC 6711为核心的虹膜图像采集系统，介绍了其工作原理、软硬件设计与实现。
This paper proposes an algorithm of iris automated identification and a method for rectification of geometric distortion of iris image. The matching result is measured by the relative coefficient.
提出了虹膜自动身份识别的算法及虹膜图像几何畸变的校正方法，最后用相关系数来测度图像的匹配结果。
Iris image quality evaluation is an important step of iris recognition, because the image quality is crucial to recognition effect.
虹膜图像质量评估是虹膜识别系统中的关键步骤，图像质量的好坏将直接影响后续识别结果的准确性。
Iris image quality evaluation is an important step of iris recognition, because the image quality is crucial to recognition effect.
虹膜图像质量评估是虹膜识别系统中的关键步骤，图像质量的好坏将直接影响后续识别结果的准确性。
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