基于八叉树编码的铸件点云融合简化方法

A Simplified Method of Casting Point Cloud Fusion Based on Octree Partitioning

高精度三维扫描设备扫描后会产生高密度的点云,对存储容量要求高,处理算法耗时长。为了减少这两方面的需求,通常采用表面简化算法作为预处理阶段。针对铸件浇冒口切割的点云简化要求,提出了一种新的点云特征融合简化方法。首先通过八叉树编码将原始点云数据分成多个边长指定的子立方体,并保留离子立方体重心最近的点;其次,使用k-邻域法来得到点云的特征向量,从而计算出点云的曲率特征,根据可调曲率阈值将点云数据划分为多个区域;最后,将随机采样方法与基于区域重心的简化方法相结合,对铸件点云数据进行简化。结果表明,所提出的铸件点云简化方法与区域重心法和包围盒法相比,速度分别提高29.9%和33.8%,而且保留的特征点分别提高15.1%、19.2%;与随机采样法相比保留的特征点提高20%,简化率基本相同。因此,此方法能够获得有效准确的铸件点云简化数据,可用于提升自动化工业生产中铸件切割的准确度和工作效率。

High-precision three-dimensional scanning equipment will produce a high-density point cloud after scanning,which requires high storage capacity and time-consuming processing algorithms.To reduce the need for both,surface simplification algorithms are usually used as a pre-processing stage.A new point cloud feature fusion simplification method is proposed in this paper for the point cloud simplification requirement of casting gate cutting.The original point cloud data is first divided into multiple sub-cubes with specified edge lengths by octree coding,and the point with the closest center of gravity of the ionic cube is retained.Then the k-neighborhood method is used to obtain the feature vectors of the point cloud,so that the curvature features of the point cloud can be calculated and the point cloud data can be divided into multiple regions according to the adjustable curvature threshold.Finally,the random sampling method is combined with the simplification method based on the regional center of gravity to simplify the casting point cloud data.The results show that the casting point cloud simplification method proposed in this paper improves the speed by 29.9%and 33.8%,and the retained feature points by 15.1%and 19.2%,respectively,compared with the regional center of gravity method and the enclosing box method,and the retained feature points by 20%compared with the random sampling method,with basically the same simplification rate.Therefore,the proposed method can obtain effective and accurate the simplification data of casting point cloud,which can be used to improve the accuracy and efficiency of casting cutting in automated industrial production.