• DocumentCode
    1633292
  • Title

    Real-time road lane recognition using fuzzy reasoning for AGV vision system

  • Author

    Kuang, Ping ; Zhu, Qingxin ; Liu, Guochan

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    2
  • fYear
    2004
  • Firstpage
    989
  • Abstract
    The automatic guided vehicle (AGV) vision system is an important research area in computer vision. In order to recognize the road lane quickly and effectively, this paper presents an algorithm using fuzzy reasoning based on the Hough transform to solve this problem, which improves the entire system´s real-time performance. After our tests on the test vehicle, this method can speed up the road lane recognition velocity phenomenally, and it also can improve the stability in driving.
  • Keywords
    Hough transforms; automatic guided vehicles; computer vision; fuzzy logic; inference mechanisms; real-time systems; AGV vision system; Hough transform; automatic guided vehicles; computer vision; fuzzy reasoning; real-time performance; road lane recognition; speed up; stability; Cameras; Computer science; Computer vision; Educational institutions; Fuzzy reasoning; Machine vision; Real time systems; Remotely operated vehicles; Road vehicles; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems, 2004. ICCCAS 2004. 2004 International Conference on
  • Print_ISBN
    0-7803-8647-7
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2004.1346345
  • Filename
    1346345