• DocumentCode
    2748111
  • Title

    Automated pavement distress detection using advanced image processing techniques

  • Author

    Sun, Y. ; Salari, E. ; Chou, E.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, Toledo, OH, USA
  • fYear
    2009
  • fDate
    7-9 June 2009
  • Firstpage
    373
  • Lastpage
    377
  • Abstract
    In this paper, a novel, fast and self-adaptive image processing method is proposed for the extraction and connection of break points of cracks in pavement images. The algorithm first finds the initial point of a crack and then determines the crack´s classification into transverse, longitudinal and alligator types. Different search algorithms are used for different types of cracks. Then the algorithm traces along the crack pixels to find the break point and then connect the identified crack point to the nearest break point in the particular search area. The nearest point then becomes the new initial point and the algorithm continues the process until reaching the end of the crack. The experimental results show that this connection algorithm is very effective in maximizing the accuracy of crack identification.
  • Keywords
    feature extraction; image classification; image resolution; object detection; road building; advanced image processing techniques; automated pavement distress detection; break points connection; break points extraction; crack classification; crack identification; crack pixels; Civil engineering; Filtering; Image processing; Image segmentation; Inspection; Remuneration; Robustness; Statistics; Sun; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electro/Information Technology, 2009. eit '09. IEEE International Conference on
  • Conference_Location
    Windsor, ON
  • Print_ISBN
    978-1-4244-3354-4
  • Electronic_ISBN
    978-1-4244-3355-1
  • Type

    conf

  • DOI
    10.1109/EIT.2009.5189645
  • Filename
    5189645