Sound Point Cloud Model Registration Algorithm for Drainage Pipeline Based on Feature Point Matching
3D reconstruction technology is becoming a key tool for obtaining comprehensive,complete and accurate information a-bout drainage pipes.Actual inspections are limited by the factors such as pipe blockage and pipe inspection protocols,resulting in dif-ferent positions,partial overlaps or gaps in the obtained sonar point cloud model,which needs to obtain a complete pipe model through alignment.At the same time,the traditional ICP algorithm has the problems of low efficiency and poor accuracy for the pipeline mod-el.Therefore,this paper proposes a point cloud alignment algorithm that combines coarse alignment based on feature point matching with improved ICP fine alignment.Firstly,the ISS feature point detection method is used to detect the model feature points,and fur-ther describe the feature points by the fast point feature histograms(FPFH);Secondly,the random sample consensus(RANSAC)al-gorithm is used to filter the correct feature matching point set,solve the initial transformation parameters by the quadratic method and complete the coarse alignment;Finally,based on the coarse alignment,the ICP algorithm with the improved nearest corresponding point query is used to complete the fine alignment.The experimental results demonstrate the feasibility and superiority of the pro-posed algorithm,which it provides a high-precision point cloud data model for the subsequent detection of tunnel defects.
sonar point cloudpoint cloud alignmentfeature matchingrandom sampling consistencyiterative nearest point
万方数据
维普
