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Fast and large-converge-radius inverse compositional Levenberg-Marquardt algorithm for digital image correlation: principle, validation, and open-source toolbox
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Biocomposites. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Biocomposites. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center.ORCID iD: 0000-0003-2566-5271
2022 (English)In: Optics and lasers in engineering, ISSN 0143-8166, E-ISSN 1873-0302, Vol. 151, article id 106930Article in journal (Refereed) Published
Abstract [en]

This paper presents an inverse compositional Levenberg-Marquardt (IC-LM) algorithm for robust, efficient, and accurate image registration in digital image correlation (DIC). In essence, the IC-LM algorithm is a mixture of the classical inverse compositional Gaussian-Newton (IC-GN) and gradient descent algorithms. Further normalization of the local coordinate and image intensity is also introduced to adaptively initialize the damping parameter in the IC-LM algorithm. The proposed IC-LM algorithm is proven to hold a larger converge radius while having comparable accuracy, precision, and efficiency compared with the classical IC-GN algorithm. The efficient reliability-guided displacement tracking strategy is also merged into the IC-LM algorithm to provide an accurate initial guess for all calculation points. For the sake of reproducibility of this algorithm, the open-source MATLAB toolbox featuring the IC-LM algorithm is available on GitHub ( https://github.com/cbbuaa/DIC _ ICLM _ MATLAB ).

Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 151, article id 106930
Keywords [en]
Digital image correlation, Inverse compositional Levenberg-Marquardt, algorithm, Converge radius, Normalization, Open-source toolbox
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-311532DOI: 10.1016/j.optlaseng.2021.106930ISI: 000779177300007Scopus ID: 2-s2.0-85121902959OAI: oai:DiVA.org:kth-311532DiVA, id: diva2:1655039
Note

QC 20220429

Available from: 2022-04-29 Created: 2022-04-29 Last updated: 2022-06-25Bibliographically approved

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Chen, BinJungstedt, Erik

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