An automatic identification of rock mass discontinuity from 3D point clouds using multi-point clustering algorithm

Key Points

• Automated identification of rock mass discontinuities can significantly improve geological assessments, enhancing accuracy and speed.
• The analysis achieved over 85% accuracy in identifying discontinuities from 3D point cloud data, validating the effectiveness of the proposed algorithm.
• Assessment using multi-point clustering algorithm delineated complex rock structures, giving detailed insights for geological studies.
• Efficiency gains in geological mapping might aid in infrastructure projects, reducing costs and time for surveys.