• DocumentCode
    569770
  • Title

    A lane boundary detection method based on high dynamic range image

  • Author

    Kou, Fei ; Chen, Weihai ; Wang, Jianhua ; Zhao, Zhiwen

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    21
  • Lastpage
    25
  • Abstract
    Every year many vehicle departure accidents happen due to the driver´s carelessness. Lane Departure Warning System (LDWS) is a kind of system which can relieve the stress of the drivers and reduce traffic accidents. But most traffic scenes have greater dynamic range than the digital camera at present. It makes the accuracy of the system would be affected by the complicated lighting. Traditional lane detection methods always use a usual image taken by the camera to detect the lane boundary. In this paper, we will use three images with different exposure to merge a high dynamic range (HDR) image and detect the lane in the HDR image. The experimental results show that the high dynamic range image can improve the accuracy of the lane detection method. However, processing of merging HDR image is very time consuming. It makes HDR image can´t be used in real-time LDWS. We proposed an improved method based on exposure fusion to reduce the computational time of the system.
  • Keywords
    alarm systems; driver information systems; image fusion; merging; object detection; road accidents; street lighting; video cameras; video surveillance; HDR image merging; LDWS; camera; exposure fusion; high dynamic range image; lane boundary detection; lane departure warning system; lighting; traffic scene; vehicle departure accident; Cameras; Dynamic range; Histograms; Image edge detection; Merging; Real time systems; Roads; Autonomous Vehicle; Computer Vision; HDR image; Lane Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-0312-5
  • Type

    conf

  • DOI
    10.1109/INDIN.2012.6301367
  • Filename
    6301367