• DocumentCode
    2872502
  • Title

    Research on Unstructured Road Detection Algorithm Based on the Machine Vision

  • Author

    Wu, Wei ; ShuFeng, Gong

  • Author_Institution
    Sch. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • Volume
    2
  • fYear
    2009
  • fDate
    18-19 July 2009
  • Firstpage
    112
  • Lastpage
    115
  • Abstract
    This paper presents an unstructured road detection algorithm which can improve the detecting speed and accuracy of unstructured road detection. In this algorithm, first, we process the original images with the median value filter, and suppress the stochastic noise; Then an Otsu multi-threshold algorithm based on two-peak method for rapid image segmentation is used, which cause the division effect and the division time to be optimum; Finally the primary edge detection with the Canny operator and mathematics morphology are used, which can obtain the complete and clear path edge image, eventually enhance the accuracy of the path examination obviously. The simulation results show that the unstructured path examination method has the good characteristics of detecting speed and accuracy.
  • Keywords
    computer vision; edge detection; image segmentation; mathematical morphology; median filters; object detection; roads; Canny operator; Otsu multithreshold algorithm; edge detection; image segmentation; machine vision; mathematics morphology; median value filter; unstructured road detection; Detection algorithms; Filters; Image edge detection; Machine vision; Mathematical model; Mathematics; Mobile robots; Morphology; Roads; Robot vision systems; Canny operator; Otsu multi-threshold algorithm; machine vision; mathematics morphology; unstructured road detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-0-7695-3699-6
  • Type

    conf

  • DOI
    10.1109/APCIP.2009.164
  • Filename
    5197149