• DocumentCode
    2407608
  • Title

    The research on video supervision technology based on mathematical morphology

  • Author

    Bin, Shao ; Yunliang, Jiang ; Zhen, Yang

  • Author_Institution
    Sch. of Inf. Eng., Zhejiang Univ., Huzhou, China
  • fYear
    2009
  • fDate
    15-16 May 2009
  • Firstpage
    57
  • Lastpage
    60
  • Abstract
    This paper studies some aspects needing to be improved in current video supervision technology. It puts forward video supervision background self-adaptive algorithm in complex environment, by using mathematical morphology, genetic algorithm, rough set theory, etc. We construct morphological structure element according with traffic moving target, and propose mathematical morphology analysis model for traffic video images. At the same time, we study feature extraction based on mathematical morphology and tracking detection methods, and establish typical violation pattern base by utilizing domain expert knowledge.
  • Keywords
    computer vision; feature extraction; genetic algorithms; knowledge based systems; mathematical morphology; object detection; road traffic; rough set theory; traffic engineering computing; video signal processing; domain expert knowledge; feature extraction; genetic algorithm; knowledge base system; mathematical morphology; road traffic video image; rough set theory; target detection; tracking detection method; video supervision background self-adaptive algorithm; Artificial intelligence; Cameras; Computerized monitoring; Educational institutions; Humans; Image analysis; Information analysis; Morphology; Target tracking; Traffic control; genetic algorithm; knowledge base; mathematical morphology; traffic supervision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-3817-4
  • Type

    conf

  • DOI
    10.1109/ICIMA.2009.5156559
  • Filename
    5156559