Rub�n Usamentiaga
An improved 3D imaging system for dimensional quality inspection of rolled products in the metal industry
Usamentiaga, Rub�n; Garc�a, Daniel F.; Bulnes, Francisco G.; Espina, Adri�n; Smith, Lyndon N.; Usamentiaga, Rube�n; Garc?�a, Daniel; Bulnes, Francisco; Espina, Adria�n; Molleda, Julio; Smith, Lyndon; Dieye, Bassiru
Authors
Daniel F. Garc�a
Francisco G. Bulnes
Adri�n Espina
Lyndon N. Smith
Rube�n Usamentiaga
Daniel Garc?�a
Francisco Bulnes
Adria�n Espina
Julio Molleda
Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine
Bassiru Dieye
Abstract
Measurement, inspection and quality control in industry have benefited from 3D techniques for imaging and visualization in recent years. The development of machine vision devices at decreased costs, as well as their miniaturization and integration in industrial processes, have accelerated the use of 3D imaging systems in industry. In this paper we describe how to improve the performance of a 3D imaging system for inline dimensional quality inspection of long, flat-rolled metal products manufactured in rolling mills we designed and developed in previous works. Two dimensional characteristics of rolled products are measured by the system: width and flatness. The system is based on active triangulation using a single-line pattern projected onto the surface of the product under inspection for range image acquisition. Taking the system calibration into account the range images are transformed into a calibrated point cloud representing the 3D surface reconstruction of the product. Two approaches to improve the line detection and extraction method used in the original system are discussed, one intended for high-speed processing with lower accuracy, and the other providing high accuracy while incurring higher computational time expenses. A mechanism to remove, or at least reduce, the effects of product movements while manufacturing, such as bouncing and flapping, is also proposed to improve the performance of the system. © 2013 Elsevier B.V. All rights reserved.
Journal Article Type | Article |
---|---|
Publication Date | Jan 1, 2013 |
Deposit Date | Aug 8, 2013 |
Journal | Computers in Industry |
Print ISSN | 0166-3615 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 64 |
Issue | 9 |
Pages | 1186-1200 |
DOI | https://doi.org/10.1016/j.compind.2013.05.002 |
Keywords | dimensional quality inspection, 3D imaging in industry, 3D surface reconstruction, line detection and extraction, active triangulation |
Public URL | https://uwe-repository.worktribe.com/output/930950 |
Publisher URL | http://dx.doi.org/10.1016/j.compind.2013.05.002 |
Contract Date | Apr 12, 2016 |
You might also like
Machine vision and deep learning for robotic harvesting of shiitake mushrooms
(2024)
Presentation / Conference Contribution
3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy
(2024)
Presentation / Conference Contribution
Estimating water storage from images
(2024)
Presentation / Conference Contribution
Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa
(2022)
Presentation / Conference Contribution
A robust machine learning framework for diabetes prediction
(2021)
Presentation / Conference Contribution
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search