An intelligent fuzzy multifactor based decision support system for crack detection of underground sewer pipelines

This paper describes a practical and reliable solution/approach to achieve a semi-automated sewer pipeline inspection. The central goal of this work is to detect faults in the sewer lines which are a potential threat for underground drainage system. The major challenge for sewer line inspection is the classification and interpretation of the image data that are captured mainly by CCTV cameras mounted on robots. In this paper we had focused on providing the human operators a tool based on image processing technology that will help them to take decision on the pipe quality. The approach in this paper involves segmentation of the sewerage images based on prior knowledge of the defects. In this paper, a multi-factorial based approach has been proposed where the decision taking process involves a fuzzy mechanism based on weighted values of different parameters.