- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | JIANG Shaofei, LI Pengze, XIANG Cheng, LIU Yantai, YU Jianlong, TIE Xinyang. Ancient Stone Arch Bridge Inverse Modeling Method Based on UAV and Image Contour Extraction[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20250183
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To achieve digital modeling and performance evaluation of ancient stone arch bridges, this study researches the reverse modeling method based on Unmanned Aerial Vehicle (UAV) oblique photography and image contour extraction technology. Firstly, a UAV is used to collect multi-view sequence images of the stone arch bridge. Secondly, the Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms are used to construct three-dimensional (3D) model of stone arch bridges. Then, based on the characteristics of color difference between stone blocks and mortar as well as the geometric regularity of stone blocks, strategies of color difference enhancement and small-area impurity filtering are proposed to improve the Canny edge detection. Cyclic quadrilateral recognition and shape optimization are introduced to improve the polygon approximation algorithm, so as to realize the automatic identification of surface contours. Subsequently, the real scale is calibrated based on ground control points, and the finite element model is generated through parametric modeling using the extracted contour coordinates. Finally, the proposed method is applied to model Toulong Bridge and analyze its performance, which is compared with experimental results. The study shows that no obvious diseases are detected on the surface of the 3D real-scene model of Toulong Bridge, with a maximum dimensional error of 0.8%; the maximum calculation error of the deflection is 2.1% by the finite element model. These indicate that the method can accurately reflect the geometric shape and mechanical properties of ancient stone arch bridges, providing technical support for their digital protection and performance evaluation.
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