• DocumentCode
    2223768
  • Title

    Robust snake model

  • Author

    Luo, Hui ; Lu, Qiang ; Acharya, R.S. ; Gaborski, R.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., State Univ. of New York, Buffalo, NY, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    452
  • Abstract
    In this paper, we propose a new deformable model a robust snake model, which solves the primary problems suffered by the conventional snake, such as contour initialization, proper internal parameter setting and the limited capture range of the external energy. A reformulated internal energy is used to serve the smoothness of snake contour without a contraction of the contour. The external energy combines both region and edge information to enlarge the capture range, and also reduces the requirement of initial contour. Both synthetic and real gray-level images are selected to evaluate the performance of the proposed model. Its implementation show it robust, fast and accurate. Initial experimental results are encouraging
  • Keywords
    computational complexity; computational geometry; image processing; contour initialization; deformable model; gray-level images; performance evaluation; reformulated internal energy; robust snake model; snake contour; synthetic images; Active contours; Computer science; Deformable models; Electrical capacitance tomography; Energy capture; Filters; Robustness; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on
  • Conference_Location
    Hilton Head Island, SC
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-0662-3
  • Type

    conf

  • DOI
    10.1109/CVPR.2000.855854
  • Filename
    855854