A Review of Image-Based Pavement Crack Detection Algorithms

Regular road surface inspection and maintenance on highways, bridges, tunnels and other transportation infrastructure are of great significance. As one of the common pavement diseases, cracks can pose a potential threat to the safety of bridges, tunnels, airports, etc., and may cause severe damage to pavements if they are not properly repaired in time. Therefore, crack detection and segmentation as well as repairing are essential to maintain the overall condition of different pavements. This paper aims to discuss the development of image-based automatic pavement crack detection algorithms as well the remaining challenges. Firstly, traditional methods that are based on spatial-domain, frequency-domain, etc. are described. Then the methods using deep learning techniques are introduced. Datasets and metrics for crack detection are introduced next. Finally, some remaining problems and the future research directions are presented.