The relative distance of key point based iris recognition
The relative distance of key point based iris recognition
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DOI：
10.1016/j.patcog.2006.03.008
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发表时间：
2007-02
期刊：
影响因子：
--
通讯作者：
Li Yu;D. Zhang;Kuanquan Wang
中科院分区：
文献类型：
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作者：
Li Yu;D. Zhang;Kuanquan Wang
虹膜识别作为一种可靠的身份识别方法，近年来受到越来越多的关注。本文尝试基于关键点的相对距离分析虹膜纹理信息的局部特征结构。在预处理时，环形虹膜被归一化为矩形块。采用多通道二维Gabor滤波器提取虹膜纹理。在每个滤波后的子图像中，我们提取每个通道中最能有效地代表局部纹理的点。每个通道中这些点的重心称为关键点，并获得一组关键点。然后，每个子图像的关键点的中心与每个关键点之间的距离称为相对距离，这被视为虹膜特征向量。虹膜特征匹配是基于欧氏距离的。在公共数据库和私有数据库上的实验结果表明，该方法的性能令人鼓舞。
Iris recognition has received increasing attention in recent years as a reliable approach to human identification. This paper makes an attempt to analyze the local feature structure of iris texture information based on the relative distance of key points. When preprocessed, the annular iris is normalized into a rectangular block. Multi-channel 2-D Gabor filters are used to capture the iris texture. In every filtered sub-image, we extract the points that can represent the local texture most effectively in each channel. The barycenter of these points in each channel is called the key point and a group of key points are obtained. Then, the distance between the center of key points of each sub-image and every key point is called relative distance, which is regarded as the iris feature vector. Iris feature matching is based on the Euclidean distance. Experimental results on public and private databases show that the performance of the proposed method is encouraging.