Abstract:When the spherical target is used as the feature point of the same name for point cloud data registration, if there is a large amount of noise in the vicinity of the target with interference or scanning target point cloud, it will have a great influence on the point cloud registration quality. In view of the current situation that the point cloud registration has neglected target self-scanning noise, the characteristics of spherical target are analyzed, the applicability of the wavelet threshold denoising method is discussed, and the method of selecting the wavelet base function is tested. A wavelet threshold denoising method of the spherical target point cloud discrete noise is proposed. Experimental results show that the denoising of the target's own point cloud cannot be neglected; the result of case analysis shows that the method can filter the rough noise near the sphere more effectively, the fitting accuracy of the center position of a single spherical target is increased by about 0.8 mm, as compared with the point cloud stitching result of the spherical target without denoising. The co-ordinate stitching distance error of the scan feature check point is reduced by about 5 mm, and the registration accuracy of the point cloud is increased by about 20%. It is an efficient preprocessing method for point cloud registration data, and can provide reference for the application of related engineering.
YU Teng,LI Mingfeng,HU Wusheng et al. Research on Spherical Target Center Location Based on Three-Dimensional Laser Scanning Point Cloud after De-Noising[J]. jgg, 2019, 39(8): 849-855.