Abstract
This paper presents the preliminary results of a research project that seeks to investigate the use of advanced image processing, computer vision and pattern recognition technologies, to facilitate asset inspection and condition assessment of sewer pipeline infrastructure. This research aims to provide a basis for sewer pipeline inspection and condition assessment, enabling automatic detection and recognition of defects and/or critical features from sewer pipeline inspection videos and images. An approach for automatic detection and recognition is presented in this paper. The major steps of the approach are illustrated by examples using actual sewer inspection visual data.
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