Fingerphoto images captured using a smartphone are successfully used to verify the individuals that have enabled several applications. This work presents a novel algorithm for fingerphoto verification using a nested residual block: Finger-NestNet. The proposed Finger-NestNet architecture is designed with three consecutive convolution blocks followed by a series of nested residual blocks to achieve reliable fingerphoto verification. This paper also presents the interpretability of the proposed method using four different visualization techniques that can shed light on the critical regions in the fingerphoto biometrics that can contribute to the reliable verification performance of the proposed method. Extensive experiments are performed on the fingerphoto dataset comprised of 196 unique fingers collected from 52 unique data subjects using an iPhone6S. Experimental results indicate the improved verification of the proposed method compared to six different existing methods with EER = 1.15%.
翻译:使用智能手机采集的手指摄影图象被成功用于验证已启用多个应用程序的个人。 这项工作展示了使用嵌套残余块( Finger- NestNet)进行手指摄影核查的新型算法。 提议的手指- NestNet 结构的设计有三个连续的卷变区块,然后是一系列嵌套残余区块,以实现可靠的手指摄影校验。 本文还介绍了拟议方法的可解释性,使用了四种不同的直观技术,可以揭示手指摄影生物鉴别学中的关键区域,有助于拟议方法的可靠核查性能。 对由使用iPhone6S从52个独特数据主体收集的196个独有手指组成的指数数据集进行了广泛的实验。 实验结果表明,与EER=1.15%的六种不同现有方法相比,对拟议方法的验证有所改善。