标题 |
RESEARCH ON IMPROVED REGION GROWING POINT CLOUD ALGORITHM
相关领域
云计算
计算机科学
点云
算法
点(几何)
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网址 | |
DOI |
10.5194/isprs-archives-XLII-3-W10-153-2020
doi
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其它 | The effective segmentation of point clouds is a prerequisite for surface reconstruction, blind spot repair, and so on. Among them, regional growth is widely used due to its simple and easy to implement algorithm. However, the traditional regional growth segmentation algorithm often causes problems such as over-segmentation or voiding of the segmentation result due to the instability of the local features of the point cloud or the unreasonable selection of the initial seed nodes. In view of the above shortcomings, this paper proposes an improved region growing point cloud algorithm. Firstly, by calculating the Gaussian curvature and the average curvature of the point cloud data and sorting them, and setting the minimum curvature point as the seed node, the total number of clusters is reduced, and the quality of the classification result is improved. Secondly, the growth of the point cloud region growth criterion is determined by combining the normal angles. |
求助人 |
如约而至 在
2021-06-30 14:27:04 发布,悬赏 10 积分
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