Boundary recognition of ship planar components from point clouds based on trimmed delaunay triangulation

A vision-based boundary detector is crucial for intelligent processing of ship planar components due to its automatically identifying workpiece edges. However, traditional methods suffer from many issues such as low accuracy and excessive detection errors for these workpieces with complex shape profiles. This paper proposes a trimmed Delaunay triangulation method (TDT) for recognizing boundary edges of planar workpieces from point clouds. It begins by distinguishing the difference of binary image pixel generated from point cloud to eliminate redundant points far away from plane boundary. Then, a triangulation trimming algorithm is developed to extract the edge points from the simplified points. Finally, complete plane boundary is reconstructed by a clustering-and-fitting method from the extracted edge points. Experimental results from multiple angles show that average absolute errors of straight edges and angles recognition are 1.29 mm and 1.04° respectively, which demonstrate that TDT has a high identification accuracy and robustness of plane boundary edge.