采用空间投影的深度图像点云分割  

Depth Image Point Cloud Segmentation Using Spatial Projection

作　　者：郭清达 全燕鸣[2] Guo Qingda;Quan Yanming(School of Electronic and Information Engineering,South China University of Technology,Guangzhou,Guangdong 510641,China;School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou,Guangdong 510641,China)

机构地区：[1]华南理工大学电子与信息学院,广东广州510641 [2]华南理工大学机械与汽车工程学院,广东广州510641

出　　处：《光学学报》2020年第18期134-142,共9页Acta Optica Sinica

基　　金：广东省重点领域研发计划(2019B010155001)。

摘　　要：点云分割是点云处理的一个关键环节,其分割质量决定了目标测量、位姿估计等任务的精确与否。提出了一种采用空间投影的深度图像(RGB-D)点云分割方法,在分析了相机模型、RGB-D数据特征以及图像阈值与目标点云关系的基础上,建立靶标坐标系与点云区域的模型,进一步地结合靶标坐标系和图像阈值,把点云变换至靶标坐标系以突出目标区域、弱化背景区域,并用图像形态学处理所投影的像素值以及分割图像以获得所对应的点云区域。建立3种测试场景以获得3组不同的点云数据,采用4种方法对点云进行分割对比,其中采用空间投影的方法能获得较高的点云分割质量;对空间投影中的膨胀元素、数值与分割质量的关系进行测试分析,结果表明了采用空间投影的方法对RGB-D点云分割的有效性和可行性。Point cloud segmentation is a key step in point cloud processing,and its segmentation quality determines the accuracy of target measurement,pose estimation,and other tasks.This paper proposes a method of depth image(RGB-D)point cloud segmentation using spatial projection.Based on the camera model,RGB-D data characteristics,and the relationship between the image threshold and the target point cloud,a target coordinate system and point cloud regions are established.Further,based on the target coordinate system and the image threshold,the point cloud is transformed to the target coordinate system to highlight the target region and weaken the background region.Also,the projected pixel values are processed by image morphology and the corresponding point cloud region is obtained by segmenting the image.Finally,three test scenarios are established to acquire three different groups of point cloud data,and four methods are adopted to segment and compare point clouds.The spatial projection based method can obtain better point cloud segmentation quality.The relationship among the expansion element,numerical value,and segmentation quality is tested and analyzed.The results show that the spatial projection method is effective and feasible for RGB-D point cloud segmentation.

关 键 词：机器视觉 点云分割 空间投影 图像阈值 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]