Point Cloud Data Processing and Analysis for 3D Measurement of Ship Hull Plate

Abstract

In this paper, the 3D measurement of the hull plate is used as the background. It analyzes the principle of laser three-dimensional scanning. The independent k-neighbor problem is considered to improve the method of law loss propagation adjustment, at point cloud data segmentation. It improves the K-neighbor point cloud data boundary feature extraction algorithm. A point cloud reduction algorithm based on K-d tree space partitioning and local curvature threshold is proposed, and the algorithm flow is given. Finally, the related algorithms are simulated and tested, and the results also verify the feasibility of the above method , meet the needs of hull plate measurement.