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.
Computer and Modernization