一种基于八邻域深度差的点云边缘提取算法
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1. 沈阳工业大学软件学院沈阳110020;2. 江苏省机电产品循环利用技术重点建设实验室常熟215500

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TH131

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江苏省机电产品循环利用技术重点建设实验室基金(KF1508)、国家自然科学基金(61540069)项目资助


8NDDbased point cloud edge extraction algorithm
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1. School of software, Shenyang University of Technology, Shenyang 110020, China; 2. Jiangsu Key Laboratory of Recycling and Reuse Technology for Mechanical and Electronic Products, Changshu 215500, China

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    摘要:

    提出了一种基于八邻域深度差(8NDD)的点云边缘提取算法。算法根据目标特征的点云,对每个特征点沿深度方向进行垂直投影并对投影点进行栅格划分,计算出每个栅格内投影点所对应深度的平均值作为该栅格的深度值;然后比较每个栅格与其八邻域栅格的深度差,根据深度差判断该栅格内是否存在边缘点,并采用排序法从栅格内筛选出目标的点云边缘点。针对含有非孔洞和孔洞的两种典型点云数据,利用八邻域深度差算法进行点云边缘提取,验证了算法的有效性。

    Abstract:

    A novel point cloud edge extraction algorithm is proposed in this paper based on eight neighbor depth difference. In this algorithm, according to the point clouds of the object features, each feature point is projected vertically along the depth direction, the projection points are divided to grids, and the average of the depths corresponding to the projection points in each grid is calculated and used as the depth of the grid. Then, the depth of each grid is compared with those of its eight neighbor grids; and according to the depth difference, whether edge point exists in the grid or not is determined, and then the sorting method is used to screen out the point cloud edge point of the object in the grid. Aiming at two typical point cloud data containing nonhole and hole, the proposed eight neighbor depth difference algorithm is used to extract the edges of point clouds, which verifies the effectiveness of the algorithm.

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张志佳,魏信,周自强,李嘉兴,王婷婷.一种基于八邻域深度差的点云边缘提取算法[J].仪器仪表学报,2017,38(8):2015-2021

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  • 在线发布日期: 2017-09-04
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