Convolutional Neural Network-based Finger Vein Recognition using Near Infrared Images

Subha Fairuz, M. H. Habaebi, E. Elsheikh, A. Chebil
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引用次数: 8

Abstract

Convolutional Neural Network (CNN) is opening new horizons in biometrics-based authentication field and finger vein recognition is the prominent one which can provide the best possible security system depending on this aforementioned technology. In this paper, we used 5 convolutional layers and 4 fully-connected layers where our developed network has shown the capability to produce the result with almost 100% accuracy rate which became possible due to the fact that deep learning, an end-to-end system is used which performs better in a lot of aspects in comparison to conventional techniques.
基于卷积神经网络的近红外图像手指静脉识别
卷积神经网络(CNN)在基于生物特征的身份认证领域开辟了新的领域,而手指静脉识别是其中的佼佼者,它可以提供最好的安全系统。在本文中,我们使用了5个卷积层和4个全连接层,其中我们开发的网络已经显示出产生几乎100%准确率的结果的能力,这是由于深度学习这一事实,使用了端到端系统,与传统技术相比,它在很多方面都表现得更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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