Point cloud quality evaluation method and device, terminal equipment and readable storage medium

By generating target point clouds and calculating the aggregate element density, a multi-level weighted calculation method is adopted to solve the problem of the singularity of point cloud quality evaluation in the existing technology, and improve the accuracy and applicability of point cloud quality evaluation. In particular, it provides a scientific point cloud density design reference in overhead transmission lines.

CN118657727BActive Publication Date: 2026-06-16NORTHWEST ENGINEERING CORPORATION LIMITED

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NORTHWEST ENGINEERING CORPORATION LIMITED
Filing Date
2024-06-05
Publication Date
2026-06-16

AI Technical Summary

Technical Problem

Existing airborne LiDAR point cloud quality evaluation methods cannot effectively reflect the number of point clouds of three-dimensional targets, resulting in relatively simple evaluation indicators. They cannot guide the refined inspection and intelligent application of UAVs, especially in overhead power transmission lines where the ground point cloud density is large but the point cloud density of the hardware is small, thus failing to provide reliable design references.

Method used

By generating target point clouds, the overall voxel density of the target ontology is calculated. A multi-level weighted calculation method is used to consider the distribution characteristics of the point cloud on different structures and to evaluate the quality of the point cloud.

Benefits of technology

It improves the accuracy and applicability of point cloud quality evaluation, provides scientific reference values ​​for point cloud density design, and is applicable to fields such as reverse engineering, quality inspection, and virtual reality modeling.

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Abstract

The application provides a point cloud quality evaluation method, device, terminal equipment and readable storage medium, and belongs to the technical field of three-dimensional measurement. In order to solve the technical problems of single point cloud quality evaluation index and low precision in the prior art, the point cloud quality evaluation method comprises the following steps: generating a target point cloud based on an original point cloud of a target ontology; calculating a comprehensive voxel density of the target ontology based on the target point cloud; and performing quality evaluation on the target point cloud according to the comprehensive voxel density to obtain a quality evaluation result. The application can effectively improve the point cloud quality evaluation precision.
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