基于点云切片改进法的不规则物体体积测量

Volume Measurement of Irregular Objects Based on Improved Point Cloud Slicing Method

现有边界点排序算法在处理具有多个轮廓边界的点云切片数据时,存在无法区分各个边界、生成异常边界多边形和截面面积计算错误等问题,导致体积测量精度较低。为此,提出一种顾及截面中多轮廓边界分割的点云切片改进法,用于不规则体体积高精度测量。该方法首先通过欧氏聚类或多边形拆分再重组法将切片中多个边界一一分开;然后由PNPoly算法理清边界多边形之间的包含关系并计算截面区域面积;最后依切片顺序累加算得点云体积(即物体体积)。采用多组数据对比分析所提两种边界分割方法的有效性和准确性,及体积测量精度和效率。实验结果表明,多边形拆分再重组方法边界分割正确率高、适用性强,且体积测量精度稳定可靠、用时少(三组数据体积计算相对误差分别为0.0901%、0.0557%和0.0289%,计算用时分别为2.229 s,33.732 s和327.476 s),达到了体积高精度测量目的。

When processing point cloud slicing data with multiple contour boundaries,the existing boundary point sorting algorithms have problems such as the inability to distinguish each boundary,generation of abnormal boundary polygons,and cross-sectional area calculation errors,which result in low volume measurement accuracy.Therefore,an improved point cloud slicing method that considers multiple contour boundary segmentation is proposed in this paper for high-accuracy volume measurement of irregular objects.In this method,the multiple boundaries are segmented by the segmentation based on euclidean clustering(SEC)method or the polygon splitting and recombination(PSR)method.Then,the inclusion relationships of the boundary polygons are clarified by the PNPoly algorithm,and the cross-sectional areas are calculated.Finally,the volume of the point cloud(that is,object volume)is calculated by accumulating the cross-sectional areas according to the slicing order.Multiple datasets are used to compare and analyze the effectiveness and correctness of the proposed two boundary segmentation methods as well as their volume measurement accuracy and efficiency.Experimental results demonstrate that the PSR method has high boundary segmentation accuracy,strong applicability,stable and reliable volume measurement accuracy(relative errors of volume calculation on three datasets are 0.0901%,0.0557%,and 0.0289%,respectively),and less calculation time(with calculation time of 2.229 s,33.732 s,and 327.476 s,respectively),thereby achieving the purpose of high-precision volume measurement.