[1] ZHANG Yiming, ZHAO Tianhao, LIAO Ruixuan, LI Haoqing, et al. An improved Alpha-shape algorithm for extracting section contours of the super-high steel bridge tower using point clouds [J]. Journal of Southeast University (English Edition), 2026, 42 (1): 26-35. [doi:10.3969/j.issn.1003-7985.2026.01.003]
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An improved Alpha-shape algorithm for extracting section contours of the super-high steel bridge tower using point clouds(
)
基于改进Alpha-shape的超高钢桥塔点云截面轮廓提取方法研究
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 42
- Issue:
- 2026 1
- Page:
- 26-35
- Research Field:
- Traffic and Transportation Engineering
- Publishing date:
- 2026-03-20
Info
- Title:
- An improved Alpha-shape algorithm for extracting section contours of the super-high steel bridge tower using point clouds
- 基于改进Alpha-shape的超高钢桥塔点云截面轮廓提取方法研究
- Author(s):
- ZHANG Yiming, ZHAO Tianhao, LIAO Ruixuan, LI Haoqing, WANG Hao
- Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education, Southeast University, Nanjing 211189, China
- Keywords:
- super-high steel bridge tower; point cloud; contour extraction; improved Alpha-shape algorithm
- PACS:
- U445
- DOI:
- 10.3969/j.issn.1003-7985.2026.01.003
- Abstract:
- The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features. Factors such as fabrication errors, gravity-induced deformations, and temperature fluctuations can compromise the accuracy of contour extraction. To address these limitations, an improved Alpha-shape-based point cloud contour extraction method is proposed. The proposed approach uses a hierarchical strategy to process three-dimensional laser scanning point clouds. The processed data are then subjected to curvature-adaptive voxel filtering to reduce acquisition noise. In addition, an enhanced iterative closest point (ICP) variant with correspondence validation accurately aligns the discrete point cloud segments. The proposed curvature-responsive Alpha-shape framework enables multiscale contour delineation through topology-adaptive threshold modulation, which resolves boundary ambiguities in geometrically complex cross-sections. The method was experimentally validated using field-acquired measurement datasets from the Zhangjinggao Yangtze River Bridge tower segments, confirming its capability to reconstruct noncanonical cross-sectional geometries. Three contour extraction methods, including Poisson reconstruction, the conventional Alpha-shape algorithm, and random sample consensus with ICP (RANSAC-ICP), were compared to evaluate the performance of the proposed Alpha-shape algorithm. The results demonstrate that the proposed method achieves superior contour extraction accuracy and data reduction efficiency, highlighting its effectiveness in contour extraction tasks.
- 高精度提取复杂截面轮廓是实现超高钢桥塔虚拟预装配的关键步骤。然而,三维激光扫描数据易受制造误差、重力变形与温度变化等因素影响,难以满足精密建模需求。为克服上述问题,本文提出一种基于改进Alpha-shape的点云轮廓提取方法,以提升复杂截面轮廓重建精度。该方法采用分层处理策略对三维激光扫描点云进行预处理,结合自适应体素滤波技术以有效抑制扫描噪声,并采用最近点迭代(ICP)算法实现节段点云的精确配准。在此基础上,引入拓扑自适应阈值调节机制,实现对多尺度复杂几何边界的精细刻画,有效改善传统方法在边界模糊区域的提取不稳定性问题。结合张靖皋长江大桥塔节段的点云实测数据对该方法进行验证,并与Poisson重建、传统Alpha-shape及基于ICP的随机样本一致性(RANSAC-ICP)方法进行对比。结果表明,所提方法在轮廓提取精度和数据简化效率方面均表现优异,验证了其在复杂截面几何重建中的适用性。
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Memo
- Memo:
-
Received: 2025-07-04; Revised: 2025-10-22.
Biographies: ZHANG Yiming(1992—), male, doctor, professor; WANG Hao (corresponding author), male, doctor, professor, wanghao1980@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China (No.52338011), the Start-up Research Fund of Southeast University (No.RF1028624058), the Southeast University Interdisciplinary Research Program for Young Scholars, the National Key Research and Development Program of China (No.2024YFC3014103).
Citation: ZHANG Yiming, ZHAO Tianhao, LIAO Ruixuan, et al. An improved Alpha-shape algorithm for extracting section contours of the super-high steel bridge tower using point clouds[J]. Journal of Southeast University (English Edition), 2026, 42(1): 26-35. DOI: 10. 3969/j. issn. 1003-7985. 2026. 01. 003.