Rockfall body discontinuous edge point extraction method and device based on improved centerline transformation

By improving the central axis transformation method and combining clustering and region growing algorithms, the discontinuous edge lines of dangerous rock masses are automatically extracted, which solves the problems of low accuracy and low efficiency in the existing technology and realizes high-precision and robust discontinuous trace extraction.

CN121904085BActive Publication Date: 2026-06-26INNOVATION ACAD FOR PRECISION MEASUREMENT SCI & TECH CAS +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
INNOVATION ACAD FOR PRECISION MEASUREMENT SCI & TECH CAS
Filing Date
2026-03-24
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies suffer from low accuracy, low efficiency, and susceptibility to subjective factors in the extraction of discontinuous features in unstable rock masses. Traditional centerline transformation methods are difficult to calculate the true centerline point in complex scenarios, resulting in inaccurate edge line extraction.

Method used

An improved median transformation method is used in combination with mean clustering, region growing algorithm and alpha-shape algorithm. By calculating the median sphere, curvature and normal of point cloud data, discontinuous edge lines are automatically extracted, including point cloud clustering, region growing and boundary point fusion.

Benefits of technology

It significantly improves the accuracy and robustness of discontinuous trace extraction, realizes full-process automation from point cloud data to discontinuous edge points of dangerous rock masses, reduces reliance on expert experience, and improves the objectivity and repeatability of results.

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Abstract

The application discloses a dangerous rock mass discontinuous edge point extraction method and equipment based on improved central axis transformation, obtains rock mass discontinuous edge line candidate points from three-dimensional point cloud data with a normal of a target region; carries out point cloud blocking on the three-dimensional point cloud data to obtain three-dimensional point cloud cluster data; calculates the curvature of the discontinuous edge line candidate points in the selected three-dimensional point cloud cluster data, separates the three-dimensional point cloud cluster data based on a region growing algorithm to obtain a separated region corresponding to each three-dimensional point cloud cluster data; extracts three-dimensional boundary point clouds of the three-dimensional point cloud cluster data and the separated region; fuses the three-dimensional boundary point clouds of the three-dimensional point cloud cluster data and the separated region and carries out filtering, and finally obtains a final dangerous rock mass discontinuous line. The application significantly improves the precision and reliability of dangerous rock mass discontinuous feature extraction, reduces the harsh requirements on the uniformity of initial data, and improves the robustness and universality under complex geological conditions and different collection environments.
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