Evaluation of cracks and disintegrations using close-range digital photogrammetry and image processing technique

Abstract

Serviceability of road pavements is continuously deteriorating due to traffic loading and poor qualities of the sub grade, sub base, base, or wearing course. To keep road pavements in good condition, maintenance and repair strategies must be based on an informed knowledge of current pavement condition. Such data are gathered by human inspectors who walk or drive along the road to assess the distresses and writing report sheets manually. This visual survey method which takes too much time and effort is too costly and compromises the safety of the field personnel. With an automated digital image processing technique of pavement distress analysis, more areas can be surveyed and the collected data can be analysed quickly. Furthermore, the automated method can improve the objectivity, accuracy, and consistency of distress survey data. This research is aimed at the development of an Automated Pavement Imaging Program (APIP) for evaluating pavement distress condition. The digital image processing program enables longitudinal, transverse, and alligator cracking to be classified. Subsequently, the program will automatically estimate the crack intensity which can be used for rating pavement distress severity. Advancement in digital photogrammetric technology creates an opportunity to overcome some problems associated with the manual methods. It can provide a low-cost, near real time geometrical imaging through digital photogrammetry without physically touching the surface being measured. Moreover, digital photogrammetry workstation (DPW) is user-friendly, less tedious and enables surface conditions to be represented as ortho-image, overlay contour with orthoimage, as well as digital elevation model. Results obtained by this technique are compared with the Jabatan Kerja Raya manual using conventional method to check accuracy. The algorithms developed in this study are capable of identifying type of cracking and its severity level at the accuracy about 90%. The combination of photogrammetric system and APIP has been shown to be capable of producing a similar accuracy to the existing system