The detection and measurement of surface properties, such as cracks and roughness, on concrete structures have been of significant interest in recent years. Crack formation, width and propagation as well as surface roughness are important indicators of the structural integrity and condition of a concrete pavement that can determine the need for an upgrade or maintenance operation in roads and bridges. The use of non-destructive testing techniques for development of analytical and numerical processing tools that enables the efficient measurement of surface properties is the aim of this work. In the proposed framework, a stereo camera set-up is utilised to map and register surface roughness of a concrete pavement. The benefit of using a depth image to create a surface map lies in its low-cost and ability to provide depth changes at a highly-refined level with approximately 0.05 mm accuracy. Concrete samples of different roughness are used to assess the viability of such technique in enhancing inspection ability and the effectiveness of robust structural health monitoring and assessment. The focus is placed on: the acquisition of spatial and visual data and creating a 3D point cloud mesh using XYZ and RGB data; an efficient algorithm for the registration and analysis of XYZ- RGB data; and accuracy assessment of stereo cameras in detection and measurement. The investigation herein outlined capitalises on the potential for stereo cameras in developing a pipeline for data acquisition, detection and measurement of cracks and surface roughness in concrete structures.

ARC DE150101703, ARC DP140100529, ARC LP140100591