深度学习技术在指纹识别中的应用  

Application of Deep Learning in Fingerprint Recognition

作　　者：李硕 赵朝阳 屈音璇 罗亚平[1] LI Shuo;ZHAO Chaoyang;QU Yinxuan;LUO Yaping(School of Investigation,People's Public Security University of China,Beijing 100038,China;Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国人民公安大学侦查学院,北京100038 [2]中国科学院自动化研究所,北京100190

出　　处：《计算机工程》2024年第12期33-47,共15页Computer Engineering

基　　金：中国人民公安大学刑事科学技术双一流创新研究专项(2023SYL06)。

摘　　要：指纹识别是应用最早、使用最成熟的一项生物特征识别技术,在民用领域的门禁考勤、移动支付以及刑侦领域检视嫌疑人线索等方面均有着广泛的应用。近年来,深度学习技术给计算机视觉以及生物特征领域带来了深刻变革,也给指纹研究人员提供了一种自动处理以及应用融合特征有效表示指纹的新方法,在指纹识别的各个阶段均有着优异的效果。概述指纹识别的发展历史与应用背景,阐述指纹识别图像预处理、特征提取以及指纹匹配3个阶段的主要处理流程,分别对深度学习技术在不同阶段的应用现状进行归纳和总结,比较不同深度神经网络在图像分割、图像增强、方向场估计、细节特征提取以及指纹匹配等具体环节的应用效果。最后,分析当前指纹识别领域存在的一些问题与挑战,并对构建公开指纹数据集、进行多尺度指纹特征提取以及训练端到端指纹识别模型等未来的发展方向进行展望。Fingerprint recognition is one of the earliest and most mature biometric recognition technologies that is widely used in mobile payments,access control and attendance in the civilian field,and in criminal investigation to retrieve clues from suspects.Recently,deep learning technology has achieved excellent application results in the field of biometric recognition,and provided fingerprint researchers with new methods for automatic processing and the application of fusion features to effectively represent fingerprints,which have excellent application results at all stages of the fingerprint recognition process.This paper outlines the development history and application background of fingerprint recognition,expounds the main processing processes of the three stages of fingerprint recognition,which are image preprocessing,feature extraction,and fingerprint matching,summarizes the application status of deep learning technology in specific links at different stages,and compares the advantages and disadvantages of different deep neural networks in specific links,such as image segmentation,image enhancement,direction field estimation,minutiae extraction,and fingerprint matching.Finally,some of the current problems and challenges in the field of fingerprint recognition are analyzed,and future development directions,such as building public fingerprint datasets,multi-scale fingerprint feature extraction,and training end-to-end fingerprint recognition models,are prospected.

关 键 词：指纹识别 深度学习 卷积神经网络 指纹自动识别系统 指纹检验 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]