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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

Jian Wang

Luca Pagani

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.

Journal Article Type Article
Publication Date 2017-01
Journal Precision Engineering
Print ISSN 0141-6359
Electronic ISSN 0141-6359
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 47
Pages 111-121
APA6 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
DOI https://doi.org/10.1016/j.precisioneng.2016.07.012
Keywords weighted fusion; multi-sensor measurement; surface reconstruction; uncertainty
Publisher URL http://www.sciencedirect.com/science/article/pii/S014163591630126X
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
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...ecisioneng.2016.07.012; Content Type: article; Copyright: © 2016 Elsevier Inc. All rights reserved.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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