Identifying and retrieving distress images from road pavement surveys

This paper proposes a system capable of identifying and retrieving distress images from a road pavement survey image database. A database of images acquired during road pavement surface surveys along Portuguese roads is considered. Regions corresponding to cracks are detected over the acquired images, based on a subdivision of the images into a set of non-overlapping windows, which may be classified as containing cracks, or not. Crack detection results, represented by binary images where windows containing crack pixels are set to one, undergo a second classification stage to distinguish several crack types. This classification follows the structure proposed by the Portuguese Distresses Catalog, produced by the national entity in charge of road maintenance. Three crack types are identified at this stage: longitudinal cracks, transversal cracks and miscellaneous cracks. The experimental results, obtained by processing real survey imagery over Portuguese roads, present encouraging results for automating the process of identifying road distresses from images.