• DocumentCode
    2486755
  • Title

    A Force Field Driven SOM for boundary detection

  • Author

    He, Yu ; Xu, Songhua ; Miranker, Willard L.

  • Author_Institution
    Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    We will introduce a method to extract object boundaries from an image. This method utilizes a deformable curve based on the Self Organizing Map algorithm. The proposed SOM has some unique properties such as batch update and neuron insertion/deletion. These properties can make the SOM converge to object concavities as well as maintain a uniform distribution of neurons along the SOM. In comparison with other traditional active contour methods, this algorithm is less sensitive to initialization more flexible in noisy conditions. It outperforms the Gradient Vector Flow method.
  • Keywords
    curve fitting; feature extraction; object detection; self-organising feature maps; boundary detection; deformable curve; force field driven SOM; object boundary extractioni; object concavities; self organizing map algorithm; Active contours; Computational modeling; Deformable models; Force; Image edge detection; Kernel; Neurons; Active Contour; Edge Detection; Self Organizing Map;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596310
  • Filename
    5596310