Long distance iris recognition

R. Amandi, Mitra Bayat, Kobra Minakhani, Hamidreza Mirloo, M. Bazarghan
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引用次数: 2

Abstract

In this paper we introduce an algorithm to analyze the human iris, long-range iris recognition software has been developed to be more user-friendliness and create an economic way to the identification. Our algorithm centralized on pupil detection, and by using estimated ranges we omit the other regions to create more efficient search space. The final decision on iris region detection provides by Hough Transform. We use the Gaussian method to create a refined mask which has an important rule of the matching process. To extract efficient features of iris regions and matching we used SIFT algorithm, Results on CASIAV4-at Distance shows %93 as verification Rate.
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远距离虹膜识别
本文介绍了一种对人体虹膜进行分析的算法,开发了远程虹膜识别软件,使虹膜识别更加人性化,为虹膜识别提供了一种经济可行的方法。我们的算法集中于瞳孔检测,并通过使用估计范围来忽略其他区域,以创造更有效的搜索空间。虹膜区域检测的最终决策由霍夫变换提供。我们使用高斯方法创建了一个精细的蒙版,它具有匹配过程的重要规则。为了有效提取虹膜区域特征并进行匹配,我们采用SIFT算法,在CASIAV4-at Distance上的验证率为%93。
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