离散数据的k近邻快速搜索算法

Zhu Ge-jun, M. Changsheng, Xie Feng
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引用次数: 2

摘要

本文提出了一种改进的离散数据k -近邻搜索算法,对逆向工程的曲面重建技术具有重要意义。首先采用传统的分块算法对点云空间进行初始分割,然后估计点云的平均点距;根据平均点距重新划分点云空间。块结果减小了k近邻搜索算法的搜索范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The K-nearest neighbor fast searching algorithm of scattered data
The paper has put forward an improved K-nearest searching algorithm of scattered data, which is significant to the technology of surface recreate of reverse engineering. Firstly, the initial segmentation of point cloud space is made by adopting the traditional block algorithm, and then estimates the average dot pitch of point cloud. Re-divide the point cloud space according to average dot pitch. The block result decreases the searching range of k-nearest neighbor searching algorithm.
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