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首页> 外文期刊>IEEE transactions on information forensics and security >Convolutional Neural Network for Finger-Vein-Based Biometric Identification
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Convolutional Neural Network for Finger-Vein-Based Biometric Identification

机译:卷积神经网络用于基于静脉的生物识别

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摘要

The use of human finger-vein traits for the purpose of automatic user recognition has gained a lot of attention in recent years. Current state-of-the-art techniques can provide relatively good performance, yet they are strongly dependent upon the quality of the analyzed finger-vein images. In this paper, we propose a convolutional-neural-network-based finger-vein identification system and investigate the capabilities of the designed network over four publicly available databases. The main purpose of this paper is to propose a deep-learning method for finger-vein identification, which is able to achieve stable and highly accurate performance when dealing with finger-vein images of different quality. The reported extensive set of experiments show that the accuracy achievable with the proposed approach can go beyond 95% correct identification rate for all the four considered publicly available databases.
机译:近年来,将人的手指静脉特征用于自动用户识别已引起了广泛关注。当前的最新技术可以提供相对较好的性能,但是它们在很大程度上取决于所分析的手指静脉图像的质量。在本文中,我们提出了一种基于卷积神经网络的手指静脉识别系统,并在四个公共数据库上研究了设计网络的功能。本文的主要目的是提出一种用于手指静脉识别的深度学习方法,该方法在处理不同质量的手指静脉图像时能够实现稳定且高度准确的性能。报告的大量实验表明,对于所有四个被认为可公开获得的数据库,该方法所能达到的准确度可以超过95%的正确识别率。

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