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A Multi Biometric System Based On The Right Iris And The Left Iris Using The Combination Of Convolutional Neural Networks

机译:一种基于右侧虹膜的多生物识别系统和左虹膜使用卷积神经网络的组合

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摘要

Biometrics to revolutionize the world of IT security. Many companies and governments and multinational corporations are opting for this technology to secure their data. In recent years we have seen the appearance of the biometric passport, the biometric driver’s license. Researchers and industrialists in the field use multimodal biometric recognition systems to increase the security and robustness of the system. Single-mode biometric systems have made their contributions, but the use of only one modality makes the system vulnerable. Biometrics professionals opt for a multimodal system. The combination can do between the following methods: facial recognition, fingerprint, iris, voice recognition, signature, etc. The biometric identification system for people in India (launched in 2009) [39] includes several steps for authentication. First, he asks for recognition of the iris, then fingerprints of the ten fingers, and finally facial recognition. In this article, we propose a system of iris recognition by the classification and the combination of the right iris and the left iris. All this done through the use of Deep Learning technology, the experiments carried out on three architectures of convolutional neural networks (CNN): VGG16 [31] [34], DenseNet169 [32] [35], Resnet50 [33] [36] with the MMU1 [37] database. We obtained excellent results with an accuracy of 100 % for the combination of the architecture ResNet50 of right iris and DenseNet169 of the left iris.
机译:生物识别学彻底改变IT安全世界。许多公司和政府和跨国公司正在选择这项技术以确保其数据。近年来,我们已经看到了生物识别护照的外观,生物识别驾驶执照。该领域的研究人员和工业家使用多模态生物识别系统来提高系统的安全性和鲁棒性。单模生物识别系统已经取得了贡献,但使用只有一个模态使系统变得脆弱。生物识别专业人员选择多式式系统。该组合可以在以下方法之间进行:面部识别,指纹,虹膜,语音识别,签名等。印度人的生物识别系统(于2009年推出)[39]包括近几个级别的认证。首先,他要求认识到虹膜,然后是十个手指的指纹,最后是面部识别。在本文中,我们通过分类和右虹膜和左虹膜的组合提出了一种虹膜识别系统。所有这一切通过使用深度学习技术完成,实验在卷积神经网络的三个架构(CNN):VGG16 [31] [34],DenSenet169 [32] [35],Resnet50 [33] [36] MMU1 [37]数据库。我们获得了良好的结果,精度为左虹膜的右侧虹膜和Densenet169的架构Reset50的组合。

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