Abstract: With the increase in traffic volume, it brings new problems to people’s live, that is, the task of inspection and maintenance of road pavements has become increasingly arduous. Therefore, the detection and identification of the road surface has become particularly urgent. This paper proposes a crack classification method based on diagonal matching of square bounding boxes. This method is used to match the geometric features of different types of cracks and gives an evaluation criterion for the regional similarity metrics that can be used to construct the classification of crack types. It provides quantitative criteria for refining the intrinsic relationship of complex types of crack areas. The experimental results show that the classification function of the crack type of the pavement is better. The results show that the accuracy of the identification and classification of block and crack cracks is obviously better than the traditional classification methods such as random forest and support vector machine.
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