Spatially Constrained Discontinuity Trace Extraction from 3D Point Clouds by Intersecting Boundaries Segmented

Discontinuity trace provides critical geological data for engineering design and construction optimization. However, current extraction methods relying on discontinuity intersection fitting are highly sensitive to the segmentation accuracy of individual discontinuity, while trace segment connectivity remains suboptimal. To address these challenges, we propose an ARCG (Adaptive Region Contour Growing) method using 3D point clouds. By dynamically adjusting parameter thresholds, our approach simultaneously extracts both discontinuities and their boundaries. We then evaluate the fitting performance of different discontinuity models using area ratios, identifying the parallelogram as the most suitable representation. The method then detects intersection lines between paired discontinuities through spatial intersection analysis, with dynamic partitioning preserving original geometric properties. Finally, a bidirectional weighted graph-based growth algorithm connects intersection lines belonging to the same discontinuity, generating the final trace results. The proposed method was validated using slope data from two case studies. Results demonstrate that, compared to existing methods and point cloud processing software, our approach achieves robust extraction of complex traces while maintaining high connectivity. Moreover, it improves computational efficiency by 48.8% without compromising trace accuracy. Thus, this method offers a novel solution for the digital characterization of rock mass discontinuity parameters.