Research on dimension measurement based on 3D point cloud

Xinmeng Wang; Xudong Li; Chenchen Yan; Huijie Zhao

doi:10.1117/12.3023325

15 February 2024 Research on dimension measurement based on 3D point cloud

Xinmeng Wang, Xudong Li, Chenchen Yan, Huijie Zhao

Proceedings Volume 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023); 130690F (2024) https://doi.org/10.1117/12.3023325
Event: International Conference on Optical and Photonic Engineering (icOPEN 2023), 2023, Singapore, Singapore

Abstract

In the manufacturing industry, the high-precision and high-efficiency dimension measurement of the large componentsisan important guarantee to improve product quality and production efficiency, but the traditional contact measurement method is low efficiency, poor accuracy, time consuming and vulnerable to human factors interference, has beenunableto meet the requirements of rapid and accurate measurement. To solve this problem, based on the three-dimensional point cloud data of large components, this paper studies the geometric feature extraction and dimension measurement methods of components. The 3D point clouds of components are preprocessed by establishing topological relationship, estimating surface normal vector and point clouds filtering for noise reduction. Geometric features of preprocessedpoint clouds are extracted, including point clouds with straight line features such as side edges and point clouds with circulararc features. The specific steps include extracting key planes by RANSAC, extracting edges of planes based onnormal vector estimation, retaining point clouds with geometric features, and dividing point clouds by Euclidean clustering. After that, the extracted point clouds with geometric features are synthesized into straight lines or circles to measurestraightness and roundness. Besides, a method is proposed to search adjacent points on the linear point clouds in order tomeasure arc length and analyze error sources and accuracy. The experimental results show that the measurement methodproposed in this paper can achieve high precision dimension measurement of the components.

Citation Download Citation

Xinmeng Wang, Xudong Li, Chenchen Yan, and Huijie Zhao "Research on dimension measurement based on 3D point cloud", Proc. SPIE 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023), 130690F (15 February 2024); https://doi.org/10.1117/12.3023325

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
14 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Point clouds

Feature extraction

Tunable filters

3D metrology

Mathematical modeling

Data modeling

Industry

Show All Keywords

Keywords/Phrases

Search In:

Publication Years