一种基于八邻域深度差的点云边缘提取算法
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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。
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.
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.
引文
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[2]李江雄,吴恩启,柯映林.基于结构光的微细管孔内表面三维重建[J].仪器仪表学报,2006,27(3):254-258.LI J X,WU E Q,KE Y L.3D Reconstruction of Smalldiameter Pipes Inner Surface Based on Structural Light[J].Chinese Journal of Scientific Instrument,2006,27(3):254-258.
[3]叶井飞,高志山,刘晓莉,等.基于Zernike多项式和径向基函数的自由曲面重构方法[J].光学学报,2014,34(8):233-241.YE J F,GAO ZH SH,LIU X L,et al.Freeform surfaces reconstruction based on Zernike polynomials and radial basis function[J].Acta Optical Sinica,2014,34(8):233-241.
[4]杨贵军,柳钦火,武文波.三维激光扫描仪曲面重构算法研究[J].仪器仪表学报,2005,26(11):1181-1183.YANG G J,LIU Q H,WU W B.Research on 3D laser scan surface reconstruction algorithms[J].Chinese Journal of Scientific Instrument,2005,26(11):1181-1183.
[5]QI C,PENG G,DENNLS B,et al.Filtering airborne laser scanning data with morphological methods[J].Photogrammetric Engineering&Remote Sensing,2007(73):175-185.
[6]蒋刚.基于SVM和空间投影的点云空洞修补方法[J].计算机工程,2009,35(22):269-271.JIANG G.Point cloud hole filling method based on SVM and space projection[J].Computer Engineering,2009,35(22):269-271.
[7]唐煜程,张明君,王浩宇,等.基于GPU的三维人脸数据动态线性快速修复[J].电子测量与仪器学报,2016,30(6):959-967.KANG Y CH,ZHANG M J,WANG H Y,et al.Fast linear recovering algorithm for low quality 3D face data based on GPU[J].Journal of Electronic Measurement and Instrument,2016,30(6):959-967.
[8]王凯,穆志纯.基于沟回结构特征的三维人耳识别方法[J].仪器仪表学报,2014,35(2):313-318.WANG K,MU ZH CH,3D human ear recognition method based on auricle structural feature[J].Chinese Journal of Scientific Instrument,2014,35(2):313-318.
[9]张志佳,尹秀萍,苑玮琦.碗形塞加工误差双目视觉在线检测方法[J].红外与激光工程,2016,45(12):261-268.ZHANG ZH J,YIN X P,YUAN W Q.An online detection method of mechanical error for bowl plug basedon binocular vision[J].Infrared and Laser Engineering,2016,45(12):261-268.
[10]徐伟恒,冯仲科,苏志芳,等.一种基于三维激光点云数据的单木树冠投影面积和树冠体积自动提取算法[J].光谱学与光谱分析,2014,34(2):465-470.XU W H,FENG ZH K,SU ZH F,et al.Automatic extraction algorithm of single tree crown projection area and canopy volume based on 3D laser point cloud data[J].Spectral and Spectral Analysis,2014,34(2):465-470.
[11]刘增益,江开勇,林俊义.散乱点云特征边缘交互提取[J].计算机工程与应用,2016,52(6):186-190.LIU Z Y,JIANG K Y,LIN J Y.Interactive extraction of boundary of specified target feature on scattered point cloud[J].Computer Engineering and Applications,2016,52(6):186-190.
[12]范启忠,陈是扦,刁燕,等.基于Alpha Shapes三维重建原理的机器人工作空间求解方法[J].机械传动,2014,38(9):27-29,59.FAN Q ZH,CHEN SH Q,DIAO Y,et al.Solution method of robot workspace based on alpha shapes 3D reconstruction principle[J].Mechanical Drive,2014,38(9):27-29,59.
[13]王宗跃,马洪超,徐宏根,等.海量点云的边缘快速提取算法[J].计算机工程与应用,2010,46(36):213-215.WANG Z Y,MA H CH,XU H G,et al.Novel algorithm for fast extracting edges from massive point clouds[J].Computer Engineering and Applications,2010,46(36):213-215.
[14]吕书明,张明磊,孙树立.基于简化和细分技术的三角网格拓扑优化方法[J].计算机辅助设计与图形学学报,2014,26(8):1225-1231.LV SH M,ZHANG M L,SUN SH L.Topological optimization for triangular mesh based on simplication and subdivision[J].Journal of Computer-Aided Design&Computer Graphics,2014,26(8):1225-1231.
[15]张志佳,魏信,周自强,等.基于Kinect的拆卸工具运动轨迹识别方法[J].制造业自动化,2016,38(12):140-145.ZHANG ZH J,WEI X,ZHOU Z Q,et al.Recognition of removal tool trajectory based on Kinect[J].Manufacturing Automation,2016,38(12):140-145.
[16]张潇予,徐熙平.基于ATOS的异形件逆向工程实现技术分析[J].电子测试,2014(10):44-45.ZHANG X Y,XU X P.The shaped pieces ATOS-based reverse engineering to achieve technical analysis[J].Electronic Test,2014(10):44-45.