• DocumentCode
    949645
  • Title

    MAC: Magnetostatic Active Contour Model

  • Author

    Xie, Xianghua ; Mirmehdi, Majid

  • Author_Institution
    Univ. of Wales Swansea, Swansea
  • Volume
    30
  • Issue
    4
  • fYear
    2008
  • fDate
    4/1/2008 12:00:00 AM
  • Firstpage
    632
  • Lastpage
    646
  • Abstract
    We propose an active contour model using an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its forces can greatly improve the active contour in capturing complex geometries and dealing with difficult initializations, weak edges, and broken boundaries. The proposed method is shown to achieve significant improvements when compared against six well-known and state-of-the-art shape recovery methods, including the geodesic snake, the generalized version of gradient vector flow (GVF) snake, the combined geodesic and GVF snake, and the charged particle model.
  • Keywords
    computational geometry; differential geometry; edge detection; image representation; object detection; MAC; charged particle model; contour representation; external force field; geodesic snake; gradient vector flow snake; hypothesized magnetic interaction; magnetostatic active contour model; magnetostatic force; object boundary; shape recovery method; Active contours; deformable model; magnetostatic forces; object segmentation; Algorithms; Artificial Intelligence; Computer Simulation; Electromagnetic Fields; Electrostatics; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Theoretical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2007.70737
  • Filename
    4359352