关键词: 道路工程；路面裂缝检测；双编码器；Sobel算子；边缘信息弥补；动态通道图卷积

Abstract: In order to improve the detection accuracy of road pavement cracks, a dual encoder pavement crack detection network based on Sobel operator bridging was proposed to address the issues such as the polymorphism of road cracks and the complexity of noise. The dual encoder consisted of two parts: original image encoding and gradient encoding, in order to solve the problem of single encoder easily losing gradient information. Firstly, the original image encoding results were computed by bridging the Sobel operator in eight directions to generate the encoding information for gradient encoding. Then, the original image encoding results and the gradient encoding results were passed through a multi-scale edge information compensation module to enhance the edge information of the cracks. Finally, dynamic channel graph convolution was introduced to obtain the topological relationships existing between channels to highlight the semantic features of important channels. The research results indicate that the proposed method achieves better results on three benchmark datasets such as DeepCrack, CamCrack789 and CFD. The composite metric ODS is 87.75%, 85.05% and 78.83% for DeepCrack, CamCrack789 and CFD datasets, respectively.

Key words: highway engineering; pavement crack detection; dual encoder; Sobel operator; edge information compensation; dynamic channel graph convolution