Segmentation of buried concrete pipe images

The enormity of the problem of deteriorating pipeline infrastructure is widely apparent. Since a complete rebuilding of the piping system is not financially realistic, municipal and utility operators require the ability to monitor the condition of buried pipes. Thus, reliable pipeline assessment and management tools are necessary to develop long term cost effective maintenance, repair, and rehabilitation programs. In this paper a simple, robust and efficient image segmentation algorithm for the automated analysis of scanned underground pipe images is presented. The algorithm consists of image pre-processing followed by a sequence of morphological operations to accurately segment pipe cracks, holes, joints, laterals, and collapsed surfaces, a crucial step in the classification of defects in underground pipes. The proposed approach can be completely automated and has been tested on five hundred scanned images of buried concrete sewer pipes from major cities in North America.