• DocumentCode
    2522399
  • Title

    Computer vision-based multiple-lane detection on straight road and in a curve

  • Author

    Jiang, Yan ; Gao, Feng ; Xu, Guoyan

  • Author_Institution
    Sch. of Transp. Sci. & Eng., BeiHang Univ., Beijing, China
  • fYear
    2010
  • fDate
    9-11 April 2010
  • Firstpage
    114
  • Lastpage
    117
  • Abstract
    A vision system was designed to detect multiple lanes on structured highway using an “estimate and detect” scheme. It detected the lane in which the vehicle was driving (the central lane) and estimated the possible position of two adjacent lanes. Then the detection was made based on these estimations. The vehicle was first recognized if it was driving on a straight road or in a curve using its GPS position and the OpenStreetMap digital map. The two cases were processed differently. For straight road, the central lane was detected in the original image using Hough transformation and a simplified perspective transformation was designed to make estimations. In the case of curve path, a complete perspective transformation was performed and the central lane was detected by scanning at each row in the top view image. The system was able to detected lane marks that were not distinct or even obstructed by other vehicles.
  • Keywords
    Global Positioning System; Hough transforms; computer vision; driver information systems; edge detection; roads; GPS position; Hough transformation; OpenStreetMap digital map; computer vision system; curve road; multiple lane detection; structured highway; Cameras; Computer vision; Data processing; Global Positioning System; Machine vision; Road transportation; Road vehicles; Stereo vision; Vehicle detection; Vehicle driving; computer vision; curve detection; image processing; multiple-lane detection; perspective transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Signal Processing (IASP), 2010 International Conference on
  • Conference_Location
    Zhejiang
  • Print_ISBN
    978-1-4244-5554-6
  • Electronic_ISBN
    978-1-4244-5556-0
  • Type

    conf

  • DOI
    10.1109/IASP.2010.5476151
  • Filename
    5476151