Automated pavement distress inspection based on 2D and 3D information

During the last few decades, many efforts have been made to produce automatic inspection systems to meet the specific requirements in assessing distress on the road surfaces using video cameras and image processing algorithms. However, due to the noisy images from pavement surfaces, limited success was accomplished. One major issue with pure video based systems is their inability to discriminate dark areas not caused by pavement distress such as tire marks, oil spills, shadows, and recent fillings. To overcome the limitation of the conventional imaging based methods, a probabilistic relaxation technique based on 3-dimensional (3D) information is proposed in this paper. The primary goal of this technique is to integrate conventional image processing techniques with stereovision technology to obtain an accurate topological structure of the road defects. Simulation results show the proposed system is effective and robust on a variety of pavement surfaces.