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A Simplification Method for Point Cloud of T-Profile Steel Plate for Shipbuilding
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According to the requirements of point cloud simplification for T-profile steel plate welding in shipbuilding, the disadvantages of the existing simplification algorithms are analyzed. In this paper, a point cloud simplification method is proposed based on octree coding and the threshold of the surface curvature feature. In this method, the original point cloud data are divided into multiple sub-cubes with specified side lengths by octree coding, and the points that are closest to the gravity center of the sub-cube are kept. The k-neighborhood method and the curvature calculation are performed in order to obtain the curvature features of the point cloud. Additionally, the point cloud data are divided into several regions based on the given adjustable curvature threshold. Finally, combining the random sampling method with the simplification method based on the regional gravity center, the T-profile point cloud data can be simplified. In this study, after obtaining the point cloud data of a T-profile plate, the proposed simplification method is compared with some other simplification methods. It is found that the proposed simplification method for the point cloud of the T-profile steel plate for shipbuilding is faster than the three existing simplification methods, while retaining more feature points and having approximately the same reduction rates.
Title: A Simplification Method for Point Cloud of T-Profile Steel Plate for Shipbuilding
Description:
According to the requirements of point cloud simplification for T-profile steel plate welding in shipbuilding, the disadvantages of the existing simplification algorithms are analyzed.
In this paper, a point cloud simplification method is proposed based on octree coding and the threshold of the surface curvature feature.
In this method, the original point cloud data are divided into multiple sub-cubes with specified side lengths by octree coding, and the points that are closest to the gravity center of the sub-cube are kept.
The k-neighborhood method and the curvature calculation are performed in order to obtain the curvature features of the point cloud.
Additionally, the point cloud data are divided into several regions based on the given adjustable curvature threshold.
Finally, combining the random sampling method with the simplification method based on the regional gravity center, the T-profile point cloud data can be simplified.
In this study, after obtaining the point cloud data of a T-profile plate, the proposed simplification method is compared with some other simplification methods.
It is found that the proposed simplification method for the point cloud of the T-profile steel plate for shipbuilding is faster than the three existing simplification methods, while retaining more feature points and having approximately the same reduction rates.
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