Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|
|
---|---|---|
Article Number | 00041 | |
Number of page(s) | 4 | |
DOI | https://doi.org/10.1051/matecconf/201713900041 | |
Published online | 05 December 2017 |
An efficient 3D point cloud data denoising algorithm for ship block visual measurement
College of Automation, Harbin Engineering University, Harbin 150001, China
* Corresponding author: hrbeu411jys@163.com
For the 3D point cloud data aquired by laser scanning measurement of ship block, an efficient denoising algorithm based on image and normal vector threshold judgement is proposed. Firstly, large scale noise points are eliminated using global threshold judgement based image, then Kuwahara filter algorithm is used for data smoothing and a denoising algorithm based on normal vector threshold judgement is proposed to eliminate noises point excluding ship manufacture sections. The experiment result demonstrates that not only the proposed denoising algorithm keeps key data points but also avoids bluring point cloud boundary and eliminates noise points effectively.
Key words: ship block measurement; / point cloud data; / denoising; / least square fitting
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.