• DocumentCode
    2190089
  • Title

    A study of the edge detection for road lane

  • Author

    Phueakjeen, Worawit ; Jindapetch, Nattha ; Kuburat, Leang ; Suvanvorn, Nikom

  • Author_Institution
    Dept. of Electr. Eng., Prince of Songkla Univ., Songkhla, Thailand
  • fYear
    2011
  • fDate
    17-19 May 2011
  • Firstpage
    995
  • Lastpage
    998
  • Abstract
    This article presents an investigation of an optimum algorithm for edge detection in order to use in the road lane detection process. The main issues, including the speed, the accuracy, and the limited resources, were taken to consider for the realization on the FPGA technology. The edge detection algorithms of Canny, Prewitt, Sobel and Roberts were compared using MATLAB. A number of road images were captured by a video camera with the image size of 640×480 pixels and the frame rate of 30 fps. In addition, a mask filter was applied to remove red, green, and blue values to help the edge detection process be more efficient. From the experimental results, the Canny algorithm was the most time consuming process, and gave too many lines outside the road lane. Among these, the Roberts algorithm is not only the smallest size, but also gained the fastest speed (3.14 times faster than the Canny algorithm) and the most accurate one to detect the lines of the actual road lanes.
  • Keywords
    edge detection; field programmable gate arrays; filtering theory; road traffic; video cameras; Canny algorithm; FPGA technology; MATLAB; Prewitt algorithm; Roberts algorithm; Sobel algorithms; edge detection algorithms; mask filter; road images; road lane detection process; video camera; Edge detection; FPGA; road lane;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2011 8th International Conference on
  • Conference_Location
    Khon Kaen
  • Print_ISBN
    978-1-4577-0425-3
  • Type

    conf

  • DOI
    10.1109/ECTICON.2011.5948010
  • Filename
    5948010