• DocumentCode
    1118767
  • Title

    Segmentation of Images Having Unimodal Distributions

  • Author

    Bhanu, Bir ; Faugeras, Olivier D.

  • Author_Institution
    Image Processing Institute and Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90007; Aeronutronic Division, Ford Aerospace and Communications Corporation, Newport Beach, CA 92660.
  • Issue
    4
  • fYear
    1982
  • fDate
    7/1/1982 12:00:00 AM
  • Firstpage
    408
  • Lastpage
    419
  • Abstract
    A gradient relaxation method based on maximizing a criterion function is studied and compared to the nonlinear probabilistic relaxation method for the purpose of segmentation of images having unimodal distributions. Although both methods provide comparable segmentation results, the gradient method has the additional advantage of providing control over the relaxation process by choosing three parameters which can be tuned to obtain the desired segmentation results at a faster rate. Examples are given on two different types of scenes.
  • Keywords
    Aerodynamics; Gradient methods; Histograms; Humans; Image processing; Image segmentation; Iterative methods; Layout; Muscles; Relaxation methods; Gradient relaxation; image segmentation; nonlinear relaxation; optimization; unimodal distribution;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.1982.4767273
  • Filename
    4767273
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1118767