| 基于K近邻和法向精度的点云精简算法 |
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| 引用本文： | 张顺岚,莫建文,邹路路.基于K近邻和法向精度的点云精简算法[J].武汉理工大学学报(交通科学与工程版),2014(3):572-575. |
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| 作者姓名： | 张顺岚 莫建文 邹路路 |
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| 作者单位： | 桂林电子科技大学信息与通信学院,桂林541004 |
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| 基金项目： | 广西自然科学基金项目（批准号：2013GXNSFAA019331,2012GXNSFAA053231,2012GXNSFBA053014,2013GXNSFDA019030）;广西教育厅科研项目（批准号：201202ZD040,201204LX146）资助 |
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| 摘 要： | 针对传统点云简化算法在精简散乱点云数据时经常丢失过多特征点的不足,提出了基于K近邻和法向精度的点云精简算法.该算法首先对输入的散乱点云数据建立K近邻索引,并剔除集群点及离群点,从而完成点云数据的预处理,然后对预处理后的数据进行Delaunay三角化,并重构三角网格面,最后依据法向精度进行非特征点剔除.仿真实验表明,该算法既能较大程度地精简点云数据,又能较好地保持原有模型的基本特征.
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| 关 键 词： | 散乱点云 K近邻 法向精度 三角网格 特征点 |
Point Cloud Simplification Algorithm Based on K Neighbor and Normal Accuracy |
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| Institution: | ZHANG Shunlan, MO Jianwen ,ZHOU Lulu (School of Information and Communication ,Guilin Univ. of Electronic and Technology, Guilin 541004, China) |
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| Abstract: | To solve the problem of features always being excessively lost in traditional point cloud simplification algorithms,apoint cloud simplification algorithm is proposed which is based on K neighbor and normal accuracy.Firstly,K neighbor index of scattered point clouds is created.And clusters and outliers are eliminated.Then the Delaunay triangulation of point clouds is created.And triangular meshs are established.At last,Non-feature points are taken out according to the normal accutacy.Simulation results show that the proposed algorithm is effective to simplify scattered point clouds,and it can keep the basic characteristics of the original model. |
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| Keywords: | scattered point clouds K neighbor normal accuracy triangular mesh feature points |
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