ABSTRACT
Closed Circuit Television (CCTV) surveys are used widely in North America to assess the structural integrity of underground sewage 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 thousand 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. Automatic recognition of various pipe defects is of considerable interest since it solves problems of fatigue, subjectivity, and ambiguity, leading to economic benefits.
