• Title of article

    Automated defect detection for sewer pipeline inspection and condition assessment

  • Author/Authors

    Guo، نويسنده , , W. and Soibelman، نويسنده , , L. and Garrett Jr.، نويسنده , , J.H.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    10
  • From page
    587
  • To page
    596
  • Abstract
    To regularly and proactively assess conditions of sewer infrastructure systems to ensure their structural integrity and continuity of services, it is critical to advance the state of automated pipeline inspection and condition assessment. Currently, a critical issue is to address realistic defect detection that deals with real sewer inspection data. This paper presents the findings of a research project that seeks to enable automated detection of defects in sewer pipelines from inspection videos and images. The need for and the challenges of automated defect detection in sewer infrastructure condition monitoring are presented. Based on a general detection and recognition model established in this paper, a change detection based approach which is tailored to solve the challenges in this sewer pipeline domain is described and illustrated through case study.
  • Keywords
    Automated defect detection , Pattern recognition , image processing , Condition assessment , Sewer pipeline , Inspection
  • Journal title
    Automation in Construction
  • Serial Year
    2009
  • Journal title
    Automation in Construction
  • Record number

    1338054