Point cloud feature-preserving denoising method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of three-dimensional measurement, and provides a point cloud feature-preserving denoising method and device, electronic equipment and a storage medium, andthe method comprises the steps: constructing a preset tree model according to point cloud data, and searching a neighborhood point set corresponding to a main data point in the point cloud data basedon the preset tree model; calculating a point normal vector of the main body data point and a centroid point of a neighborhood point set according to the neighborhood point set corresponding to the main body data point through a preset algorithm; calculating a vector and a projection distance of the vector on the point normal vector according to the centroid point and the neighborhood point set;and if the projection distance satisfies a threshold distance, recording a to-be-denoised point corresponding to the projection distance as a noise point, and updating the neighborhood point set basedon the noise point until the neighborhood point set of the updated main data point is completely denoised. According to the invention, small ball-shaped noise and strip-shaped small-segment trace convex noise around the point cloud main body can be denoised, and the denoising efficiency is improved.

Description

Technical field[0001]The invention relates to the technical field of three-dimensional measurement, in particular to a point cloud feature-preserving denoising method, device, electronic equipment and storage medium.Background technique[0002]At present, in the field of 3D measurement, 3D point cloud denoising technology has important applications in reverse engineering. For 3D scanning, due to the scanning environment, scanner operation problems, scanner accuracy, etc., the acquired 3D point cloud data often contains many noise points and outliers, which will directly affect the extraction of point cloud features, point cloud splicing and 3D surface Rebuild quality. The existing point cloud denoising technology can handle noise that deviates from the main body of the point cloud at a certain distance and a long distance. For small clusters of noise around the main body of the point cloud, the denoising effect is poor, and the use of a bilateral filtering algorithm will change the po...

AI Technical Summary

Problems solved by technology

It can be seen that in the prior art, there is a problem of low denoising efficiency for the small blob noise around the main body of the point cloud

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