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
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
Journal title :
Automation in Construction