Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Segmentation using Snakes on Digital Endoscopic Image

Snake를 이용한 디지털 내시경 영상의 분할

  • Yoon, S.W. (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, J.H. (Dept. of Electronic Communication, Shinheung College) ;
  • Choi, J.J. (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Yoon, Y.S. (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Lee, J.Y. (Dept. of Electronic Engineering, Myongji College) ;
  • Lee, M.H. (Dept. of Electrical and Electronic Engineering, Yonsei University)
  • 윤성원 (연세대학교 전기전자공학과) ;
  • 김정훈 (신흥대학 전자통신과) ;
  • 최종주 (연세대학교 전기전자공학과) ;
  • 윤용수 (연세대학교 전기전자공학과) ;
  • 이준영 (명지전문대 전자과) ;
  • 이명호 (연세대학교 전기전자공학과)
  • Published : 2002.07.10
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Abstract

Image segmentation is an essential technique of image analysis. In spite of the issues in contour initialization and boundary concavities, active contour models(snakes) are popular and successful methods for the segmentation. In this paper, we present a new active contour model, GGF snake, for segmentation of endoscopic image. The GGF snake is less sensitive to contour initialization and ensures high accuracy, large capture range, and fast CPU time for computing external force. It was observed that the GGF snake produced more reasonable results in various image types, such as simple synthetic images, commercial digital camera images, and endoscopic images than previous snakes did.

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