• DocumentCode
    507334
  • Title

    A Fast Segmentation Method Based on Curve Evolution Model and Edgeflow

  • Author

    Xie Qing-Song ; Li Jin-jiang ; Yuan Da

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Shandong Inst. of Bus. & Technol., Yantai, China
  • Volume
    5
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    307
  • Lastpage
    310
  • Abstract
    This paper proposes a high-accuracy edge contour extraction algorithm based on curve evolution model and edgeflow. The approach automatically detect boundaries, and change of topology in terms of the edgeflow fields. We present the numerical implementation and the experimental results based on the semi-implicit method. Experimental results are given to demonstrate the feasibility of the proposed method in extracting contour from the blurred edge and high-noise images.
  • Keywords
    edge detection; image segmentation; blurred edge; curve evolution model; edgeflow; fast segmentation method; high-accuracy edge contour extraction; high-noise images; semi-implicit method; Change detection algorithms; Computer science; Deconvolution; Filtering; Filters; Fuzzy systems; Image edge detection; Iterative methods; Partial differential equations; Topology; Curve Evolution; Edgeflow; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.80
  • Filename
    5360611