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IRIS recognition using conventional approach

机译:使用传统方法识别IRIS

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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:如今,我们许多社会,金融和政治结构的正常运作都取决于对人的正确识别。可靠而独特的身份识别是一个难题。人们通常使用身份证,用户名或密码来证明自己的身份,但是密码可能会被忘记,并且身份证可能会丢失或被盗。基于人的身体或行为特征来识别人的生物识别方法之所以引起人们的兴趣,是因为人们不会以丢失密码或身份证的方式忘记或失去其身体特征。已经基于指纹,面部特征,语音,手部几何形状,笔迹,视网膜以及这项工作中提出的虹膜开发了生物识别系统。由于预处理和分割阶段,虹膜是一个难题。换句话说,以矩形图像格式准备虹膜是一个复杂的问题。这项工作集中于细分问题。良好的细分反映出功能最少的完美识别。仅使用三个功能,即可实现100%识别。介绍了不同方法之间的比较研究。这项研究表明了该模型的有效性。

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