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IRIS recognition using conventional approach

机译:虹膜识别使用常规方法

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摘要

The proper functioning of many of our social, financial, and political structures nowadays relies on the correct identification of people. Reliable and unique identification of people is a difficult problem; people typically use identification cards, usernames, or passwords to prove their identities, however passwords can be forgotten, and identification cards can be lost or stolen. Biometric methods, which identify people based on physical or behavioural characteristics, are of interest because people cannot forget or lose their physical characteristics in the way that they can lose passwords or identity cards. Biometric systems have been developed based on fingerprints, facial features, voice, hand geometry, handwriting, the retina, and the one presented in this work, the iris. Iris is difficult issue because of pre-processing and segmentation phases. In other word, preparing the iris in a rectangular image format is a complicated issue. This work concentrates on segmentation issue. A good segmentation reflects on perfect recognition with minimum number of features. With only three features, 100% recognition can be achieved. A comparative study between different methodologies is introduced. This study shows the efficiency of the proposed model.
机译:我们的许多社会,经济和政治结构中的正常运作时下依赖于正确识别的人。可靠的和唯一标识的人来说是一个困难的问题;人们通常使用身份证,用户名或密码来证明自己的身份,但密码可以被遗忘,和身份证可能丢失或被盗。生物识别方法,其识别基于物理或行为特征的人,是有意义的,因为人们不能忘记或丢失,因为它们可能会失去密码或身份证的方式其物理特性。基于指纹,面部特征,语音,手形,手写,视网膜,和一个在这项工作中提出,虹膜生物识别系统已被开发。虹膜是因为前处理和分割阶段的难题。换句话说,在一个矩形图像格式制备虹膜是一个复杂的问题。这项工作集中在分割的问题。一个好的分割反映了与功能最小数量完美的认可。由于只有三个特点,100%的识别就可以实现。介绍了不同方法之间的比较研究。这项研究表明该模型的有效性。

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