An Accurate Registration Algorithm for Airborne LiDAR Point Clouds in Urban Scenes Based on the Plane Geometric Feature Constraint
Aiming at the current problems of poor automation,low efficiency and easy convergence to local optimal solution in the registration process for urban airborne LiDAR point clouds,a point cloud registration algorithm based on the plane geometric feature constraint is proposed in this paper.Firstly,the non-ground points are extrac-ted by progressive morphological filtering algorithm,and the building points are separated from the non-ground point according to the planarity and roughness of the point clouds,and then the building roof planes are segmented through the European clustering and RANSAC algorithm.Secondly,the similarity coefficient matrix of planar fea-tures is constructed by calculating the KD tree and Hausdorff distance,and the bidirectional consistency constraint rule is introduced to match the plane feathers with the cosine similarity measurement of the normal vectors.Finally,the quaternion coordinate transformation model of point clouds is established according to the constraint of planar geometric features.The experimental results show that the matching efficiency,accuracy and registration precision of the proposed algorithm are significantly improved compared with those of the traditional method of manually se-lecting the correspondence planes.
LiDAR point cloudplane featureHausdorff distancegeometric feature constraintspoint cloud reg-istration
万方数据
维普
