Laser & Optoelectronics Progress, Volume. 59, Issue 8, 0820002(2022)
Three-Dimensional Circular Hole Recognition Algorithm Based on Point Cloud Normal and Projection Fusion
This paper proposes a three-dimensional (3D) circular hole recognition algorithm based on the fusion of point cloud normal and projection to solve the problems of poor extraction accuracy and the incomplete edge point extraction of the existing 3D circular hole recognition algorithms. Firstly, k-dimensional tree(KD-tree) assists in establishing the spatial topological relationship of the point cloud. Secondly, K-NearestNeighbor(KNN) is used to search the k neighborhood points closest to the point. The point greater than the threshold is determined as the boundary point by defining the distance threshold. Finally, the fusion of point cloud normal and projection are combined to realize the distinction between feature points and noise points at the edge of the point cloud, and the 3D circular hole features of the point cloud data are extracted. The experimental results show that the algorithm can effectively realize point cloud edge extraction and 3D circular hole recognition.
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Haoyu Li, Yunjie Yang, Hao Yang, Yu Fang. Three-Dimensional Circular Hole Recognition Algorithm Based on Point Cloud Normal and Projection Fusion[J]. Laser & Optoelectronics Progress, 2022, 59(8): 0820002
Category: Optics in Computing
Received: Aug. 9, 2021
Accepted: Sep. 10, 2021
Published Online: Apr. 11, 2022
The Author Email: Fang Yu (fangyu_hit@126.com)