• DocumentCode
    3600258
  • Title

    Loop-free snakes for image segmentation

  • Author

    Ji, Lilian ; Yan, Hong

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
  • Volume
    3
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    193
  • Abstract
    Snakes are an effective approach to image segmentation. However self-looping is a very common problem that makes snakes fail to work well in certain circumstances. In order to achieve robust segmentation, this paper introduces the loop-free snakes based on an attractable active contour model that overcomes several problems of conventional snake model while retaining all properties associated with it. The proposed method can quickly and efficiently remove all loops during the evolution of snake deformation and can be less sensitive to its parameter setting and flow into more complicated contours such as long tube shapes, sharp corners, deep concave/convex shapes. Hence the new method extends the topologic flexibility and adaptability of snakes. Experiments have been conducted to segment real images with encouraging results
  • Keywords
    computational geometry; image segmentation; attractable active contour model; contours; image segmentation; loop-free snakes; self-looping; Active contours; Australia; Deformable models; Grid computing; Image converters; Image segmentation; Image storage; Shape; Sorting; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
  • Print_ISBN
    0-7803-5467-2
  • Type

    conf

  • DOI
    10.1109/ICIP.1999.817099
  • Filename
    817099