摘要
掌静脉识别作为一种新兴的红外生物识别技术,因其高安全性、活体检测性等优势已成为当前生物特征识别领域中的研究热点之一。近年来,该领域的大量研究通过引入深度学习方法推动了掌静脉识别技术的发展。为了掌握掌静脉识别领域最新研究现状及发展方向,对数据采集和数据预处理的主流算法进行了分类和总结,并针对基于深度学习的掌静脉识别的最新进展按照掌脉特征表征、网络设计与优化、轻量级网络进行了分类和详细阐述。针对当前单模态识别达到瓶颈等问题,分析并对比了多模态和多特征融合识别相关算法;探讨了当前掌静脉识别的研究难点挑战,并对未来的发展趋势进行了展望与总结。
Palm vein recognition,as a new infrared biometrics technology,has become one of the research hotspots in the field of biometric recognition because of its advantages of high security and liveness detection.In recent years,a great deal of research in this field has promoted the development of palm vein recognition technology by introducing deep learning methods.In order to grasp the latest research status and development direction in the field of palm vein recognition,data acquisition and the mainstream algorithms of data pre-processing are classified and summarized,and the latest progress of palm vein recognition based on deep learning is classified and elaborated in terms of palm vein feature representation,network design and optimization,and lightweight network.In view of the bottleneck of single-modal recognition,the correlation algorithms of multimodal and multi-feature fusion recognition are analyzed and compared.The difficulties and challenges of current research on palm vein recognition are discussed,and the future development trends are prospected and summarized.
作者
谭振林
刘子良
黄蔼权
陈荟慧
钟勇
TAN Zhenlin;LIU Ziliang;HUANG Aiquan;CHEN Huihui;ZHONG Yong(School of Electronic Information Engineering,Foshan University,Foshan,Guangdong 528225,China)
出处
《计算机工程与应用》
CSCD
北大核心
2024年第6期55-67,共13页
Computer Engineering and Applications
基金
广东省教育厅重点专项(2022ZDZX1026)。
关键词
掌静脉识别
深度学习
多模态融合
palm vein recognition
deep learning
multimodal fusion