Jian Wang
Study of weighted fusion methods for the measurement of surface geometry
Wang, Jian; Pagani, Luca; Leach, Richard K.; Zeng, Wenhan; Colosimo, Bianca M.; Zhou, Liping
Authors
Luca Pagani
Professor RICHARD LEACH RICHARD.LEACH@NOTTINGHAM.AC.UK
CHAIR IN METROLOGY
Wenhan Zeng
Bianca M. Colosimo
Liping Zhou
Abstract
© 2016 Elsevier Inc. Four types of weighted fusion methods, including pixel-level, least-squares, parametrical and non-parametrical, have been classified and theoretically analysed in this study. In particular, the uncertainty propagation of the weighted least-squares fusion was analysed and its relation to the Kalman filter was studied. In cooperation with different fitting models, these four weighted fusion methods can be applied to a range of measurement challenges. The experimental results of this study show that the four weighted fusion methods compose a computationally efficient and reliable system for multi-sensor measurement problems, especially for freeform surface measurement. A comparison of weighted fusion with residual approximation-based fusion has also been conducted by providing the input datasets with different noise levels and sample sizes. The results demonstrated that weighted fusion and residual approximation-based fusion are complementary approaches applicable to most fusion scenarios.
Citation
Wang, J., Pagani, L., Leach, R. K., Zeng, W., Colosimo, B. M., & Zhou, L. (2017). Study of weighted fusion methods for the measurement of surface geometry. Precision Engineering, 47, 111-121. https://doi.org/10.1016/j.precisioneng.2016.07.012
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 26, 2016 |
Online Publication Date | Jul 29, 2016 |
Publication Date | 2017-01 |
Deposit Date | Aug 2, 2016 |
Publicly Available Date | Aug 2, 2016 |
Journal | Precision Engineering |
Print ISSN | 0141-6359 |
Electronic ISSN | 0141-6359 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 47 |
Pages | 111-121 |
DOI | https://doi.org/10.1016/j.precisioneng.2016.07.012 |
Keywords | weighted fusion; multi-sensor measurement; surface reconstruction; uncertainty |
Public URL | https://nottingham-repository.worktribe.com/output/742158 |
Publisher URL | http://www.sciencedirect.com/science/article/pii/S014163591630126X |
Additional Information | This article is maintained by: Elsevier; Article Title: Study of weighted fusion methods for the measurement of surface geometry; Journal Title: Precision Engineering; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.precisioneng.2016.07.012; Content Type: article; Copyright: © 2016 Elsevier Inc. All rights reserved. |
Contract Date | Aug 2, 2016 |
Files
fushion.pdf
(1.2 Mb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
You might also like
Evaluating approximate and rigorous scattering models in virtual coherence scanning interferometry for improved surface topography measurement
(2024)
Presentation / Conference Contribution
Extracting focus variation data from coherence scanning interferometric measurements
(2024)
Journal Article
Comparison of Fourier optics-based methods for modeling coherence scanning interferometry
(2024)
Journal Article
Vision-based detection and coordinate metrology of a spatially encoded multi-sphere artefact
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.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