Research on Point Cloud Noise Reduction Method for Aerospace Die Forgings Based on Gaussian Curvature
In order to avoid excessive smoothing and loss of edge feature points during the high-efficiency noise reduction pro-cess for the massive 3D point cloud data of the full-surface large-scale die forging structure,this paper proposes a regional bilateral point cloud noise reduction method based on Gaussian curvature.First,the scattered point cloud is rasterized for down-sampling to eliminate the first type of noise points.Then the point cloud is divided into regions based on Gaussian curvature,while the Euclide-an distance weight is added to maintain the spatial characteristics of the point cloud,and this improved bilateral filtering way is for removing the second type of noise.Finally,on the open source PCL1.10.1 platform,the effectiveness of the point cloud noise reduc-tion method in this paper is verified.The trial shows that this point cloud filtering way can reduce the noise of the point cloud while avoiding excessive smoothing of the surface and maintaining edge features.
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