基于反馈Hough变换的管道点云检测和识别

管道是流程工厂的主体,其几何形状表现为圆柱体或圆台。针对现有管道检测识别方法对噪声较为敏感、检测精度不高、检测结果难以验证等问题,本文提出一种具有轴向反馈修正的三维霍夫变换方法。首先,根据八叉树划分点云空间,计算点云法向量并生成圆柱体或圆台高斯映射图,利用三维霍夫变换法估计初始轴向;然后,基于初始轴向计算圆柱体横截面或圆台投影轮廓,并建立轴向优化目标函数,通过迭代优化获得最终的轴向;最后通过霍夫变换法拟合圆柱体或圆台轴心位置并计算半径值。实验结果表明,该方法可有效提高管道轴向、半径等参数的估算准确度,同时,本文提出的优化目标函数也为检测结果提供了一种新的评价方法。

Detection and Recognition of Pipeline Point Cloud Based on Feedback Hough Transform

Pipeline is the main body of a processing factory, and its geometry is represented as a cylinder or a truncated cone. However, the existing methods of pipeline detection and identification are sensitive to noise and the accuracy of detection is also not high. Moreover, the detection results of the existing methods are difficult to verify. This paper proposes a 3D Hough transform algorithm with orientation feedback correction to detect and identify the pipelines of a processing factory. Firstly, the point cloud space is divided according to the Octree. The point cloud normal vector is calculated and the Gaussian map of a cylinder or a truncated cone is generated, and the initial orientation is estimated by the 3D Hough transform method. Then, the cylindrical cross section or the truncated cone projection profile is calculated based on the initial orientation. The orientation optimization objective function is established, and the final orientation is obtained through iterative optimization. Finally, the axis position of the cylinder or the truncated cone is fitted by Hough transform method and the radius value is computed. The experiments show that the proposed method can effectively improve the estimation accuracy of the parameters such as orientation and radius of the pipeline. At the same time, the optimization objective function presented in this paper also provides a new evaluation method for the detection results.