Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 1-11.doi: 10.11896/jsjkx.210400056

• Smart Healthcare • Previous Articles     Next Articles

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).

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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

CLC Number: 

  • TP391
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