It is of great scientific and practical value to use effective technical means to monitor and warn the structural damage of bridges in real time and for a long time. Traditional image recognition network models are often limited by the lack of on-site images. In order to solve the problem of automatic recognition and parameter acquisition in digital images of bridge structures in the absence of data information, this paper proposes an automatic identification method for bridge structure damage areas based on digital images, which effectively achieves contour carving and quantitative characterization of bridge structure damage areas. Firstly, the digital image features of the bridge structure damage area are defined. By making full use of the feature that the pixel value of the damaged area is obviously different from that of the surrounding image, an image pre-processing method of the structure damaged area that can effectively improve the quality of the field shot image is proposed. Then, an improved Ostu method is proposed to organically fuse the global and local threshold features of the image to achieve the damaged area contour carving of the bridge structure surface image. The scale of damage area, the proportion of damage area and the calculation rule of damage area orientation are constructed. The key inspection and characteristic parameter diagnosis of bridge structure damage area are realized. Finally, test and analysis are carried out in combination with an actual project case. The results show that the method proposed in this paper is feasible and stable, which can improve the damage area measurement accuracy of the current bridge structure. The method can provide more data support for the detection and maintenance of the bridge structure.
© 2023. The Author(s).