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Sewer pipe deformation assessment by image analysis of video surveys
A system for the practical use of computer vision techniques is presented for the automatic assessment of the structural condition of sewers from video images. The system can provide accuracy, efficiency and economy of sewer pipe examination. The main efforts of the paper have been placed on investigations of algorithms and techniques for image processing, pipe-joint shape analysis and discrimination, and crack detection. Experiments show that over 85% of the pipe-joint boundaries can be extracted successfully from video images, and for pipe-joints with very low aspect ratio (AP<0.05), the measurement error in AP is no more than 0.01. This kind of accuracy is of great significance in sewer pipe structural surveys, and cannot be achieved by visual inspection of the video images.
Sewer pipe deformation assessment by image analysis of video surveys
A system for the practical use of computer vision techniques is presented for the automatic assessment of the structural condition of sewers from video images. The system can provide accuracy, efficiency and economy of sewer pipe examination. The main efforts of the paper have been placed on investigations of algorithms and techniques for image processing, pipe-joint shape analysis and discrimination, and crack detection. Experiments show that over 85% of the pipe-joint boundaries can be extracted successfully from video images, and for pipe-joints with very low aspect ratio (AP<0.05), the measurement error in AP is no more than 0.01. This kind of accuracy is of great significance in sewer pipe structural surveys, and cannot be achieved by visual inspection of the video images.
Sewer pipe deformation assessment by image analysis of video surveys
Kun Xu (author) / Luxmoore, A.R. (author) / Davies, T. (author)
Pattern Recognition ; 31 ; 169-180
1998
12 Seiten, 10 Quellen
Article (Journal)
English
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