多阈值提取平面点云边界点的方法

针对基于切片技术的点云数据重建算法需要提取切片内点云边界点，及现有算法效率低、提取效果不好等问题，提出一种多阈值提取平面点云边界点的算法。通过选取判断点的k个近邻点，计算相邻两点与判断点连线间夹角，由于边界点必存在最大夹角，通过判断最大夹角是否超过设定阈值，从而快速提取边界点。通过对阈值设值分析，不同点云数据的边界提取实验及几种方法间比较，该方法不受点云形状影响，均能较好提取边界点，且优于其他3种算法。结果表明该方法在保证原始点云特征信息的前提下，可较好提取边界点，提高后续点云重建速度与效率。

Boundary points extraction method of planar point cloud based on multi-threshold

The method of point cloud reconstruction based on slicing technology needs to extract boundary points from slicing planar points. In order to solve the problem of extracting boundary points and overcome the drawback of low efficiency and bad result of current algorithms, a boundary points extraction method of planar point cloud based on multi-threshold was proposed. In the algorithm, k adjacent points were selected from the judged points, then the angle between the nearest points were calculated and the maximum angle was limited because there existed the biggest angle, thus the boundary points could be rapidly extracted. By analyzing the value of multi-threshold, testing the method to extract boundary points of different point cloud and comparing the proposed method with other three methods, the method accurately and better extracted boundary points regardless of the shapes. The experimental results show that the proposed method can well extract the boundary points on the condition of guaranteeing the original characteristic information and improves the speed and efficiency of point cloud reconstruction.