• DocumentCode
    680578
  • Title

    The applications of automatic vision detection for the intersections

  • Author

    Chung-Cheng Chiu ; Sheng-Yi Chiu ; Meng-Liang Chung ; Bing-Fei Wu

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Nat. Defense Univ., Taoyuan, Taiwan
  • fYear
    2013
  • fDate
    2-4 Dec. 2013
  • Firstpage
    164
  • Lastpage
    169
  • Abstract
    The intelligent transportation systems (ITS) aim to provide services to transport and traffic management and supply more information and safer to various users. The visual-based systems are the most popular solutions for ITS due to their highly maintainable, flexible, and intuitive features. This paper uses a background extraction algorithm to extract initial color backgrounds from surveillance video based on an entropy-analysis concept. The moving objects can then be segmented quickly and correctly by a robust object segmentation algorithm. The segmented object can be used to analyze the trajectory and to provide the collision between pedestrian and moving vehicle. A license plate detection algorithm is also provided to detect the license plate in this study.
  • Keywords
    computer vision; entropy; feature extraction; image colour analysis; image motion analysis; image segmentation; intelligent transportation systems; object detection; pedestrians; video surveillance; ITS; automatic vision detection; entropy-analysis concept; initial color background extraction algorithm; intelligent transportation systems; intersections detection; license plate detection algorithm; moving vehicle; object segmentation algorithm; pedestrian; surveillance video; traffic management; visual-based systems; Cameras; Image color analysis; Image segmentation; Licenses; Object segmentation; Trajectory; Vehicles; collision detection; initial background detection; license plate detection; object segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Control Conference (CACS), 2013 CACS International
  • Conference_Location
    Nantou
  • Print_ISBN
    978-1-4799-2384-7
  • Type

    conf

  • DOI
    10.1109/CACS.2013.6734126
  • Filename
    6734126