Fast 3D laser scanning of highly reflective surfaces based on a dual-camera system

Existing laser scanning approaches for highly reflective surfaces generally require multiple scans to cope with specular reflection. This paper proposes a dual-camera, line-laser scanning strategy to reconstruct them efficiently, which only needs a single scanning path. To bypass complicated point cloud processing algorithms for outlier elimination, a feasible image processing scheme was designed to delete the disturbed stripe regions. By merging two sets of point clouds computed from residual stripes on a common world frame, these removed noise patches can be compensated by the opposite camera. Therefore, the data fusion result can reconstruct the 3D geometry of targets completely. Experimental results demonstrate good performance with the ability to handle highly reflective surfaces. The scanning period is significantly shortened and scanning accuracy can meet the industrial requirement.