Abstract: Cracks on airport pavement are extremely fine, and depth camera based crack detection technology is faced with the interference from both complex pavement apparent structure and severe vibration of the platform. To handle this problem, a main profile modeling algorithm by combining L2 regularization and dynamic threshold greedy strategy is proposed to achieve accurate crack detection results of millimeter level. Firstly, the main profile of pavement is modelled constrained with L2 regularization, thus overcoming the overfitting problem caused by the complex apparent structure. Secondly, an improved greedy algorithm based on dynamic threshold is proposed to suppress noise interference by iteratively removing abnormal points caused by platform vibration. Finally, based on the constructed main profile model, the multidirection main profiles of the airport pavement are extracted and fused, and the crack depth and morphology information are used to extract the crack. Experiments on real airport pavement data show that the proposed algorithm can reconstruct the main profile of the pavement accurately, detect the fine cracks successfully, and have better crack detection performance than the existing techniques.

Key words: airport pavement, crack detection, 3D rang data, L2 regularization, greedy strategy, main profile extraction