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Hand Shape Classification using Contour Distribution

윤곽 분포를 이용한 이미지 기반의 손모양 인식 기술

  • Lee, Changmin (School of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, DaeEun (School of Electrical and Electronic Engineering, Yonsei University)
  • 이창민 (연세대학교 전기전자공학과) ;
  • 김대은 (연세대학교 전기전자공학과)
  • Received : 2014.02.15
  • Accepted : 2014.03.30
  • Published : 2014.06.01

Abstract

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

Keywords

References

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