Palm vein for efficient person recognition based on 2D gabor filter

Jixing Wang, Yuqing He*, Jiadan Zhu, Xinru Gao, Yongsheng Cui

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Palm vein recognition is a relatively new method in biometrics. This paper presents an effective palm vein feature extraction approach for improving the efficiency of palm vein identification. In this paper, relevant preprocessing steps as rotation and extraction of the Region of Interest are presented. In feature extraction, multiple 2D Gabor filters with 4 orientations are employed to extract the phase information on a palm vein image, which is then merged into unique feature according to an encoding rule. Hamming distance is used for vein recognition. Experiments are carried on a selfmade palm vein database. Experimental results show that the method in this paper achieved a higher correct recognition rate and a faster speed.

Original languageEnglish
Title of host publicationBiometric and Surveillance Technology for Human and Activity Identification X
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventBiometric and Surveillance Technology for Human and Activity Identification X - Baltimore, MD, United States
Duration: 2 May 20132 May 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8712
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceBiometric and Surveillance Technology for Human and Activity Identification X
Country/TerritoryUnited States
CityBaltimore, MD
Period2/05/132/05/13

Keywords

  • Feature coding
  • Gabor filter
  • Hamming distance
  • Palm vein
  • Pattern recognition

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