Individual authentication through hand posture recognition using Multi-Hilbert Scanning Distance

Jegoon Ryu, Sei Ichiro Kamata

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

Abstract

In this paper, we propose a novel Hand Posture Recognition (HPR) for biometrics. This study uses the three dimensional point clouds for robust hand posture recognition at the rotation and scale. Multi-Hilbert Scanning Distance (MHSD) are also introduced for mathematical approaches of shape matching. HPR framework is divided into five parts: detecting hand region, removing the wrist, aligning the hand pose, extracting feature descriptor, and matching. Based on the experimental results, this framework showed superior results for hand posture recognition rate.

Original languageEnglish
Title of host publicationProceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1787-1790
Number of pages4
ISBN (Print)9781467310680
Publication statusPublished - 2012
Event20th European Signal Processing Conference, EUSIPCO 2012 - Bucharest, Romania
Duration: 2012 Aug 272012 Aug 31

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Conference

Conference20th European Signal Processing Conference, EUSIPCO 2012
Country/TerritoryRomania
CityBucharest
Period12/8/2712/8/31

Keywords

  • Biometrics
  • Hand Posture Recognition (HPR)
  • Hilbert Scanning
  • Multi-Hilbert Scanning Distance (MHSD)

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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