• DocumentCode
    3515479
  • Title

    Automated analysis and detection of cracks in underground scanned pipes

  • Author

    Fieguth, Paul W. ; Sinha, Sunil K.

  • Author_Institution
    Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
  • Volume
    4
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    395
  • Abstract
    Closed circuit television (CCTV) surveys are used widely in North America to assess the structural integrity of underground pipes. The video images are examined visually and classified into grades according to degrees of damage. The human eye is extremely effective at recognition and classification, but it is not suitable for assessing pipe defects in thousands of miles of pipeline images due to fatigue, subjectivity and cost. This paper presents ongoing research into the automatic assessment of the structural condition of underground pipes for the purpose of preventive maintenance by municipalities
  • Keywords
    civil engineering computing; closed circuit television; crack detection; feature extraction; image classification; maintenance engineering; video signal processing; CCTV; closed circuit television; crack analysis; crack detection; feature extraction; image classification; image recognition; pipe defects; preventive maintenance; underground pipe structural integrity; underground scanned pipes; video images; Cameras; Computer vision; Image analysis; Image edge detection; Inspection; Investments; Pipelines; Radar detection; System analysis and design; TV;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    0-7803-5467-2
  • Type

    conf

  • DOI
    10.1109/ICIP.1999.819622
  • Filename
    819622