• DocumentCode
    314359
  • Title

    Range image segmentation using an oscillatory network

  • Author

    Liu, Xiuwen ; Wang, DeLiang

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
  • Volume
    3
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    1656
  • Abstract
    We use a locally excitatory globally inhibitory oscillator network (LEGION) as a framework for range image segmentation. Each oscillator in the LEGION network has excitatory lateral connections to the oscillators in its neighborhood as well as a connection with a global inhibitor. The lateral connection between two oscillators is established based on the similarity between their feature vectors which consist of the surface normal and curvature at the corresponding pixel locations. The emergent behavior of the LEGION network gives rise to the segmentation result. Unlike other methods, our scheme needs no assumption about the underlying structures in image data and no prior knowledge regarding the number of regions. Experimental results for real range images are presented
  • Keywords
    feature extraction; image segmentation; least squares approximations; neural nets; parameter estimation; excitatory lateral connections; feature vectors; locally excitatory globally inhibitory oscillator network; range image segmentation; Clustering algorithms; Cognitive science; Computer networks; Image segmentation; Information science; Inhibitors; Local oscillators; Neural networks; Organizing; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614143
  • Filename
    614143