• DocumentCode
    1566505
  • Title

    Increasing Object Recognition Rate using Reinforced Segmentation

  • Author

    Sahba, Farshid ; Tizhoosh, Hamid R. ; Salama, Magdy M. A.

  • Author_Institution
    Syst. Design Eng., Waterloo Univ., Ont., Canada
  • fYear
    2006
  • Firstpage
    781
  • Lastpage
    784
  • Abstract
    In this paper a new approach to object extraction and recognition based on reinforcement learning is presented. We use this novel idea as a method to optimally segment the image and increase the recognition rate. The success rate is compared with a classical approach. Preliminary results demonstrate increase in recognition rate.
  • Keywords
    feature extraction; image segmentation; learning (artificial intelligence); object recognition; image segmentation; object extraction; object recognition; reinforcement learning; Data mining; Design engineering; Image recognition; Image segmentation; Laboratories; Learning; Machine intelligence; Object detection; Object recognition; Pattern analysis; Image segmentation; Learning systems; Object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.312518
  • Filename
    4106646