• DocumentCode
    2620048
  • Title

    Closed-loop adaptive image segmentation

  • Author

    Bhanu, Bir ; Ming, John ; Lee, Sungkee

  • Author_Institution
    Dept. of Electr. Eng., California Univ., Riverside, CA, USA
  • fYear
    1991
  • fDate
    3-6 Jun 1991
  • Firstpage
    734
  • Lastpage
    735
  • Abstract
    A closed-loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions is presented. The genetic algorithm efficiently searches the hyperspace of segmentation parameter combinations to determine the parameter set which maximizes the segmentation quality criteria. A summary of the experimental results that demonstrates the ability to perform adaptive image segmentation and to learn from experience using a collection of outdoor color imagery is given
  • Keywords
    genetic algorithms; pattern recognition; picture processing; self-adjusting systems; adaptive image segmentation; closed-loop image segmentation system; computer vision; genetic algorithm; image characteristics; outdoor color imagery; quality criteria; Adaptive systems; Application software; Color; Computer science; Computer vision; Current measurement; Genetic algorithms; Humans; Image segmentation; Learning systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2148-6
  • Type

    conf

  • DOI
    10.1109/CVPR.1991.139805
  • Filename
    139805