Laser radar three-dimensional point cloud segmentation method

Abstract

The invention discloses a laser radar three-dimensional point cloud segmentation method. The method comprises the following steps of firstly, extracting original three-dimensional point cloud data collected by a laser radar; preprocessing the original point cloud with steps of denoising, simplifying and coordinate transformation of original point cloud data; constructing basic point cloud data under a three-dimensional Cartesian coordinate system; storing the three-dimensional data in the form of a two-dimensional array; adopting a variable neighborhood decentralized search strategy to dynamically adjust the resolution of the neighborhood range and the search matching range of the seeds surrounded by the region growing method. Point cloud preliminary segmentation work is carried out, on the basis, a point cloud segmentation envelope diffusion strategy is designed, the periphery of a point cloud segmentation set is further searched, fusion of multiple sets is achieved, then the point cloud segmentation set is obtained, and finally a visualization function of a point cloud segmentation result is designed and used for checking the point cloud segmentation effect. The method effectively improves the segmentation rate, effectively suppresses the over-segmentation condition, maintains the integrity of each target, and facilitates the observation of the scanning result of the segmented target.

Description

technical field [0001] The present invention relates to the technical field of computer vision, in particular to a method for segmenting laser radar 3D point clouds, which can be used to quickly segment three-dimensional point cloud data into independent point cloud sets. Background technique [0002] With the development of science and technology, the acquisition of surrounding information by ships during driving has gradually expanded from two-dimensional images based on optical imaging to three-dimensional images based on laser scanning. , small size, light weight and other characteristics have been widely used as sensors for 3D point cloud data acquisition, and are gradually popularized and installed at the height of ship masts. However, the original 3D point cloud data obtained by lidar cannot directly reflect the surrounding ships, and point cloud segmentation is required The result of point cloud segmentation directly affects the subsequent use of point cloud. Therefo...

AI Technical Summary

Problems solved by technology

In the process of 3D point cloud segmentation, most of the above literatures deal with the speed or stability of point cloud segmentation in a targeted manner, but the segmentation accuracy of point cloud is not ideal, especially in the point cloud segmentation of marine laser radar, which is not effective. To deal with the problem of under-segmentation of point clouds caused by mutual occlusion of multiple ships, and the problem of over-segmentation of point clouds caused by large ships being close to the lidar, so a fast and accurate method for segmenting 3D point clouds of marine lidar is needed

Images