• DocumentCode
    2865386
  • Title

    An Image Segmentation Method Based on the Improved Snake Model

  • Author

    Wang, Kejun ; Guo, Qingchang ; Zhuang, Dayan

  • Author_Institution
    Dept. of Autom., Harbin Eng. Univ.
  • fYear
    2006
  • fDate
    25-28 June 2006
  • Firstpage
    532
  • Lastpage
    536
  • Abstract
    Getting the contour of the object based on the snake model is an important method in the image segmentation. In this paper the authors first introduce the theory of the traditional snake model. A new snake model based on a dot which is in the object is proposed for avoiding some drawbacks in the traditional snake model. The algorithm not only inherits the topology ability of the traditional snake, but also has the ability of convergence to the concave, and the convergent rate is also added. The segmentation effort of the algorithm is proved by experiments
  • Keywords
    computer vision; image segmentation; topology; concave convergence; image segmentation; object contour; snake model; topology; Active contours; Automation; Convergence; Equations; Image converters; Image segmentation; Mechatronics; Solid modeling; Topology; snake model image segmentation topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on
  • Conference_Location
    Luoyang, Henan
  • Print_ISBN
    1-4244-0465-7
  • Electronic_ISBN
    1-4244-0466-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2006.257609
  • Filename
    4026139