• DocumentCode
    2706364
  • Title

    An intelligent and attractable active contour model for boundary extraction

  • Author

    Ji, Lilian ; Yan, Hong

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
  • Volume
    6
  • fYear
    1999
  • fDate
    15-19 Mar 1999
  • Firstpage
    3309
  • Abstract
    An intelligent and attractable active contour model for boundary extraction is presented in this paper. The proposed model is capable of driving any initial guess in the area of the evolving estimate towards the desired boundary, working against a constant image background, overcoming spurious edge-points and fitting into the object without any overrun. It is also capable of extracting both concave and convex boundaries while still being capable of bearing subjective boundaries with help of a synthetic convergent criterion and an adaptable interpolation scheme. Using additional two control parameters, it is possible to control the convergent properties of the new model, which provides a high degree of flexibility and adaptability. This robust model has been applied to real images with encouraging results
  • Keywords
    convergence of numerical methods; edge detection; interpolation; adaptable interpolation scheme; boundary extraction; concave boundaries; constant image background; control parameter; convergent properties; convex boundaries; initial guess; intelligent attractable active contour model; real images; spurious edge-points; subjective boundaries; synthetic convergent criterion; Active contours; Data mining; Image converters; Image edge detection; Image segmentation; Mechanical factors; Potential energy; Robustness; Shape; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
  • Conference_Location
    Phoenix, AZ
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-5041-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1999.757549
  • Filename
    757549