Palmprint recognition using valley features

Xiang Qian Wu, Kuan Quan Wang, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

Abstract

This paper presents a novel approach for palmprint recognition based on the valley features. This approach uses the bothat operation to extract the valleys from a very low-resolution palm image in different directions to form the valley feature, and then define a matching score to measure the similarity of the valley features. The experimental results shows that the proposed approach can effectively discriminate palmprints and can obtain about 98% accuracy in palmprint verification.
Original languageEnglish
Title of host publication2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Pages4881-4885
Number of pages5
Publication statusPublished - 12 Dec 2005
EventInternational Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China
Duration: 18 Aug 200521 Aug 2005

Conference

ConferenceInternational Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/TerritoryChina
CityGuangzhou
Period18/08/0521/08/05

Keywords

  • Biometrics
  • Morphological operator
  • Palmprint recognition
  • Valley feature

ASJC Scopus subject areas

  • Engineering(all)

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