Stereo Digital Image Correlation in MATLAB

Digital Image Correlation (DIC) has found widespread use in measuring full-field displacements and deformations experienced by a body from images captured of it. Stereo-DIC has received significantly more attention than two-dimensional (2D) DIC since it can account for out-of-plane displacements. Al...

Full description

Bibliographic Details
Main Authors: Devan Atkinson, Thorsten Hermann Becker
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/11/4904
_version_ 1797532535813570560
author Devan Atkinson
Thorsten Hermann Becker
author_facet Devan Atkinson
Thorsten Hermann Becker
author_sort Devan Atkinson
collection DOAJ
description Digital Image Correlation (DIC) has found widespread use in measuring full-field displacements and deformations experienced by a body from images captured of it. Stereo-DIC has received significantly more attention than two-dimensional (2D) DIC since it can account for out-of-plane displacements. Although many aspects of Stereo-DIC that are shared in common with 2D DIC are well documented, there is a lack of resources that cover the theory of Stereo-DIC. Furthermore, publications which do detail aspects of the theory do not detail its implementation in practice. This literature gap makes it difficult for newcomers to the field of DIC to gain a deep understanding of the Stereo-DIC process, although this knowledge is necessary to contribute to the development of the field by either furthering its capabilities or adapting it for novel applications. This gap in literature acts as a barrier thereby limiting the development rate of Stereo-DIC. This paper attempts to address this by presenting the theory of a subset-based Stereo-DIC framework that is predominantly consistent with the current state-of-the-art. The framework is implemented in practice as a 202 line MATLAB code. Validation of the framework shows that it performs on par with well-established Stereo-DIC algorithms, indicating it is sufficiently reliable for practical use. Although the framework is designed to serve as an educational resource, its modularity and validation make it attractive as a means to further the capabilities of DIC.
first_indexed 2024-03-10T11:00:36Z
format Article
id doaj.art-8b765226e3b04819bc82e9dd7657a7d8
institution Directory Open Access Journal
issn 2076-3417
language English
last_indexed 2024-03-10T11:00:36Z
publishDate 2021-05-01
publisher MDPI AG
record_format Article
series Applied Sciences
spelling doaj.art-8b765226e3b04819bc82e9dd7657a7d82023-11-21T21:31:17ZengMDPI AGApplied Sciences2076-34172021-05-011111490410.3390/app11114904Stereo Digital Image Correlation in MATLABDevan Atkinson0Thorsten Hermann Becker1Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Corner of Banghoek and Joubert Street, Stellenbosch 7599, Western Cape, South AfricaDepartment of Mechanical and Mechatronic Engineering, Stellenbosch University, Corner of Banghoek and Joubert Street, Stellenbosch 7599, Western Cape, South AfricaDigital Image Correlation (DIC) has found widespread use in measuring full-field displacements and deformations experienced by a body from images captured of it. Stereo-DIC has received significantly more attention than two-dimensional (2D) DIC since it can account for out-of-plane displacements. Although many aspects of Stereo-DIC that are shared in common with 2D DIC are well documented, there is a lack of resources that cover the theory of Stereo-DIC. Furthermore, publications which do detail aspects of the theory do not detail its implementation in practice. This literature gap makes it difficult for newcomers to the field of DIC to gain a deep understanding of the Stereo-DIC process, although this knowledge is necessary to contribute to the development of the field by either furthering its capabilities or adapting it for novel applications. This gap in literature acts as a barrier thereby limiting the development rate of Stereo-DIC. This paper attempts to address this by presenting the theory of a subset-based Stereo-DIC framework that is predominantly consistent with the current state-of-the-art. The framework is implemented in practice as a 202 line MATLAB code. Validation of the framework shows that it performs on par with well-established Stereo-DIC algorithms, indicating it is sufficiently reliable for practical use. Although the framework is designed to serve as an educational resource, its modularity and validation make it attractive as a means to further the capabilities of DIC.https://www.mdpi.com/2076-3417/11/11/4904digital image correlationstereosubset-basededucationMATLAB codethree-dimensional
spellingShingle Devan Atkinson
Thorsten Hermann Becker
Stereo Digital Image Correlation in MATLAB
Applied Sciences
digital image correlation
stereo
subset-based
education
MATLAB code
three-dimensional
title Stereo Digital Image Correlation in MATLAB
title_full Stereo Digital Image Correlation in MATLAB
title_fullStr Stereo Digital Image Correlation in MATLAB
title_full_unstemmed Stereo Digital Image Correlation in MATLAB
title_short Stereo Digital Image Correlation in MATLAB
title_sort stereo digital image correlation in matlab
topic digital image correlation
stereo
subset-based
education
MATLAB code
three-dimensional
url https://www.mdpi.com/2076-3417/11/11/4904
work_keys_str_mv AT devanatkinson stereodigitalimagecorrelationinmatlab
AT thorstenhermannbecker stereodigitalimagecorrelationinmatlab