• DocumentCode
    2580372
  • Title

    The use of TurSOM for color image segmentation

  • Author

    Beaton, Derek ; Valova, Iren ; MacLean, Dan

  • Author_Institution
    James J Kaput Center for Res. & Innovation in Math. Educ., Univ. of Massachusetts Dartmouth, Fairhaven, MA, USA
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    4232
  • Lastpage
    4237
  • Abstract
    This work presents an application of TurSOM for high-dimensional segmentation and cluster identification. TurSOM is a variation algorithm of the SOM algorithm, which introduces a new mechanism of self-organization: connection reorganization. We have theoretically presented TurSOM in very recent previous work, however, the applicability of the novel architecture is expanding as we explore it numerous advantages and possibilities. The intent of these experiments, and TurSOM itself, is to be able to segment and identify various distinct objects in color data (red, green, blue).
  • Keywords
    image colour analysis; image segmentation; pattern clustering; self-organising feature maps; variational techniques; TurSOM; cluster identification; color image segmentation; connection reorganization; self-organizing map; variation algorithm; Clustering algorithms; Color; Computer science education; Cybernetics; Image segmentation; Information science; Mathematics; Neurons; Technological innovation; USA Councils; Self-organizing Maps; Turing Unorganized Machines; clustering; segmentation; unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346822
  • Filename
    5346822