• DocumentCode
    3183530
  • Title

    Fuzzy logic and the principle of least commitment in computer vision

  • Author

    Keller, James M. ; Gader, Paul

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO, USA
  • Volume
    5
  • fYear
    1995
  • fDate
    22-25 Oct 1995
  • Firstpage
    4621
  • Abstract
    The application of fuzzy logic to computer vision processes has grown rapidly. The appeal of such techniques stems, at least partially, from the fact that they naturally maintain multiple hypotheses to varying degrees until a crisp decision must be made. This satisfies the principle of least commitment, originally stated by David Man for the development of intelligent computer vision algorithms. In this paper, we demonstrate fuzzy set theory´s support of this principle with three examples from midlevel vision
  • Keywords
    character recognition; computer vision; fuzzy logic; fuzzy neural nets; fuzzy set theory; object recognition; computer vision; fuzzy logic; fuzzy neural networks; fuzzy set theory; intelligent vision; least commitment principle; object recognition; Additive noise; Application software; Books; Character recognition; Computer vision; Fuzzy logic; Fuzzy set theory; Handwriting recognition; Image segmentation; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-2559-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1995.538524
  • Filename
    538524