计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 1-11.doi: 10.11896/jsjkx.210400056

• 智慧医疗 • 上一篇    下一篇


刘伟业, 鲁慧民, 李玉鹏, 马宁   

  1. 长春工业大学计算机科学与工程学院 长春 130102
  • 出版日期:2022-06-10 发布日期:2022-06-08
  • 通讯作者: 鲁慧民(luhuimin@ccut.edu.cn)
  • 作者简介:(liuweiyede@163.com)
  • 基金资助:

Survey on Finger Vein Recognition Research

LIU Wei-ye, LU Hui-min, LI Yu-peng, MA Ning   

  1. School of Computer Science and Engineering,Changchun University of Technology,Changchun 130102,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:LIU Wei-ye,born in 1995,postgraduate,is a member of China Computer Federation.His main research interests include image recognition and deep learning.
    LU Hui-min,born in 1972,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include intelligent data processing and biometric authentication.
  • Supported by:
    Key Research and Development Program of Jilin Provincial Science and Technology Development Plan in 2020(20200401103GX).

摘要: 指静脉识别因其具有活体识别、高安全性、内部特征等技术优势,已成为生物特征识别领域的研究热点之一。文中首先阐述了指静脉识别技术的基本原理及研究现状,然后针对指静脉识别过程中的主要技术,包括图像采集、传统识别方法中的图像预处理、特征提取、特征匹配,以及基于深度学习的指静脉识别,结合相关理论研究逐阶段展开论述,并对代表性的识别算法进行了概括、分析和评述。此外,全面梳理并详细介绍了指静脉识别领域常用的公开数据集,以及识别系统的相关技术评价指标,总结了指静脉识别研究尚存的主要问题,并提出了可行的解决方案,最后对指静脉识别未来的研究方向进行了展望,为后续指静脉识别的发展提供研究思路。

关键词: 深度学习, 生物特征识别, 特征提取, 图像处理, 指静脉识别

Abstract: Finger vein recognition has become one of the most popular research hotpots in the field of biometrics because of its unique technical advantages such as living body recognition,high security and inner features.Firstly,this paper introduces the principle,merits,and current research status of finger vein recognition,then making the time as the clue,sorts out the development history of finger vein recognition technology,and discusses the classical and state-of-the-art recognition algorithms.Secondly,focusing on each process of finger vein recognition,this paper expounds on the critical techniques including image acquisition,image preprocessing,feature extraction and matching in traditional methods,and deep learning-based recognition.Besides,the commonly used public datasets and the related evaluation metrics in this field are introduced.Thirdly,this paper summarizes the existing research problems,proposes the corresponding feasible solutions,and predicts the future research direction of finger vein recognition.Some new ideas in the following studies for researchers are provided at the end.

Key words: Biometrics, Deep learning, Feature extraction, Finger vein recognition, Image processing


  • TP391
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