• DocumentCode
    27449
  • Title

    Robust local–global SOM-based ACM

  • Author

    Abdelsamea, M.M. ; Gnecco, G.

  • Author_Institution
    IMT Inst. for Adv. Studies, Lucca, Italy
  • Volume
    51
  • Issue
    2
  • fYear
    2015
  • fDate
    1 22 2015
  • Firstpage
    142
  • Lastpage
    143
  • Abstract
    A novel active contour model (ACM) for image segmentation, driven by both local and global image-intensity information encoded by a self-organising map (SOM), is proposed. Experimental results demonstrate the robustness of the proposed model to the contour initialisation and to the additive noise, when compared with the state-of-the-art local and global ACMs. They also demonstrate its robustness to scene changes.
  • Keywords
    Gaussian noise; image segmentation; self-organising feature maps; active contour model; additive Gaussian noise; contour initialisation; image segmentation; image-intensity information; robust local-global SOM-based ACM; scene changes; self-organising map;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2014.3691
  • Filename
    7014469