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Digital Assisted Image Correlation for Metal Sheet Strain Measurement

Current methods of correlation and point matching between stereoscopic images produce large errors or are completely inefficient when the surface has a repetitive, non-isotropic, low contrast pattern. In this article a new method of Digital Assisted Image Correlation (DAIC) is presented to match spe...

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Autores principales: Carlos-Eduardo, García-Alcalá, José-Alfredo, Padilla-Medina, Alejandro-Israel, Barranco-Gutiérrez
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297596/
http://dx.doi.org/10.1007/978-3-030-49076-8_16
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author Carlos-Eduardo, García-Alcalá
José-Alfredo, Padilla-Medina
Alejandro-Israel, Barranco-Gutiérrez
author_facet Carlos-Eduardo, García-Alcalá
José-Alfredo, Padilla-Medina
Alejandro-Israel, Barranco-Gutiérrez
author_sort Carlos-Eduardo, García-Alcalá
collection PubMed
description Current methods of correlation and point matching between stereoscopic images produce large errors or are completely inefficient when the surface has a repetitive, non-isotropic, low contrast pattern. In this article a new method of Digital Assisted Image Correlation (DAIC) is presented to match specific points in order to estimate the deformation of the surface in the metal sheets used in the automotive industry. To achieve this, it is necessary to stamp the surface to be measured with a regular pattern of points, then a digital image processing is done to obtain the labels of the circles of the pattern. After this, a semi-automatic search is made in the labels of both images to correlate all of them and perform the triangulation. DIC is used to corroborate the correspondence between points and verify the accuracy and efficiency of the developed method. This allows the 3D reconstruction of the sheet with a minimum of information and provides more efficiency and a great benefit in computational cost. Deformation is calculated by two methods, which show similarity between the values obtained with a digital microscope. It is assumed that quality of marks stamping, lighting, and the initial conditions, also contribute for trustworthy effects.
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spelling pubmed-72975962020-06-17 Digital Assisted Image Correlation for Metal Sheet Strain Measurement Carlos-Eduardo, García-Alcalá José-Alfredo, Padilla-Medina Alejandro-Israel, Barranco-Gutiérrez Pattern Recognition Article Current methods of correlation and point matching between stereoscopic images produce large errors or are completely inefficient when the surface has a repetitive, non-isotropic, low contrast pattern. In this article a new method of Digital Assisted Image Correlation (DAIC) is presented to match specific points in order to estimate the deformation of the surface in the metal sheets used in the automotive industry. To achieve this, it is necessary to stamp the surface to be measured with a regular pattern of points, then a digital image processing is done to obtain the labels of the circles of the pattern. After this, a semi-automatic search is made in the labels of both images to correlate all of them and perform the triangulation. DIC is used to corroborate the correspondence between points and verify the accuracy and efficiency of the developed method. This allows the 3D reconstruction of the sheet with a minimum of information and provides more efficiency and a great benefit in computational cost. Deformation is calculated by two methods, which show similarity between the values obtained with a digital microscope. It is assumed that quality of marks stamping, lighting, and the initial conditions, also contribute for trustworthy effects. 2020-04-29 /pmc/articles/PMC7297596/ http://dx.doi.org/10.1007/978-3-030-49076-8_16 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Carlos-Eduardo, García-Alcalá
José-Alfredo, Padilla-Medina
Alejandro-Israel, Barranco-Gutiérrez
Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title_full Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title_fullStr Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title_full_unstemmed Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title_short Digital Assisted Image Correlation for Metal Sheet Strain Measurement
title_sort digital assisted image correlation for metal sheet strain measurement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297596/
http://dx.doi.org/10.1007/978-3-030-49076-8_16
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