基于散乱点云边界提取及简化的单坐标搜索法之改进

摘要

针对单坐标搜索法在处理大量点云数据时会出现收敛速率降低、边界提取模糊等缺点,采用一种改进的方法能快速确定点云的紧邻信息.并且在保留所有边界点的基础上,结合测点的曲率特征以及邻域内保留点的情况提取点云的边界特征并进行非均匀化.结果表明,该方法能够在快速、有效地简化点云数据的同时保持原始特征信息.%According to tranditional single-axis seching method's flaws,a improved single axes searching method is used to gain the information of K-nearest neighbors of the points reserved, simplifies the other points according to the curvature and the proportion of reserved points in their K-nearest neighbors. The sesult shows that the method can quickly and effectively simplify the point cloud data at the same time to maintain the original features.