Performance improvement of phase-based correspondence matching for palmprint recognition

Vincent Roux, Shoichiro Aoyama, Koichi Ito, Takafumi Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

The use of phase-based correspondence matching for biometric recognition makes it possible to find corresponding point pairs between images having nonlinear deformation. On the other hand, the optimal recognition performance cannot be exhibited due to simple approaches for matching score calculation and reference point placement. This paper proposes two techniques to improve performance of phase-based correspondencematching for contactless palmprint recognition. First technique analyzes location of corresponding points and defines a new matching score. Second one selects location of reference points suggested by a Difference of Gaussians (DoG) filter. Through a set of experiments using CASIA contactless palmprint database, we demonstrate that the proposed techniques improve performance of phase-based correspondence matching and exhibit good performance compared with conventional palmprint recognition algorithms.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
PublisherIEEE Computer Society
Pages70-77
Number of pages8
ISBN (Electronic)9781479943098, 9781479943098
DOIs
Publication statusPublished - 2014 Sep 24
Event2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014 - Columbus, United States
Duration: 2014 Jun 232014 Jun 28

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Other

Other2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
CountryUnited States
CityColumbus
Period14/6/2314/6/28

Keywords

  • biometrics
  • correspondence matching
  • palmprint
  • phase-only correlation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Roux, V., Aoyama, S., Ito, K., & Aoki, T. (2014). Performance improvement of phase-based correspondence matching for palmprint recognition. In Proceedings - 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014 (pp. 70-77). [6909961] (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2014.16