<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e65" altimg="si1.svg"><mml:mi mathvariant="normal">μ</mml:mi></mml:math>DIC: An open-source toolkit for digital image correlation

Olufsen, Sindre Nordmark; Andersen, Marius Endre; Fagerholt, Egil

doi:10.1016/j.softx.2019.100391

Cited by 42 publications

(12 citation statements)

References 23 publications

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“…Then it tries to establish a mapping between the image coordinates of the reference (undeformed) object image and the image coordinates of the deformed object image by searching for the mapping which gives the highest correlation between the reference image and the current image. The mapping is then used for calculating full-field strains [ 35 ].…”

Section: Methodsmentioning

confidence: 99%

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2D Digital Image Correlation and Region-Based Convolutional Neural Network in Monitoring and Evaluation of Surface Cracks in Concrete Structural Elements

Słoński

Tekieli

2020

Materials

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This paper shows how 2D digital image correlation (2D DIC) and region-based convolutional neural network (R-CNN) can be combined for image-based automated monitoring and assessment of surface crack development of concrete structural elements during laboratory quasi-static tests. In the presented approach, the 2D DIC-based monitoring enables estimation of deformation fields on the surface of the concrete element and measurements of crack width. Moreover, the R-CNN model provides unmanned simultaneous detection and localization of multiple cracks in the images. The results show that the automatic monitoring and evaluation of crack development in concrete structural elements is possible with high accuracy and reliability.

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Section: Methodsmentioning

confidence: 99%

“…Illustration of the basic principle of the digital image correlation method: sketch of the subset (a,c) and measurement points on the surface of a specimen (b,d) before (a,b) and after (c,d) deformation[36].…”

mentioning

confidence: 99%

2D Digital Image Correlation and Region-Based Convolutional Neural Network in Monitoring and Evaluation of Surface Cracks in Concrete Structural Elements

Słoński

Tekieli

2020

Materials

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“…There are several commercial software available in the market including Correlated Solutions [ 55 ], GOM Correlate [ 56 ], MatchID [ 57 ], LaVision [ 58 ] and Eikosim [ 59 ]. Open-source codes have also been developed such as Ncorr [ 60 ], DICe [ 61 ], DIC [ 62 ], multiDIC [ 63 ], pyxel [ 64 ], py2DIC [ 65 ], UFreckles [ 66 ] and YADICS [ 67 ]. In the subset-based approach, the reference (or undeformed) image is typically divided into subsets with may overlap by a step size.…”

Section: In Situ Monitoring Using Full-field Measurement Techniquementioning

confidence: 99%

In Situ Monitoring of Additive Manufacturing Using Digital Image Correlation: A Review

2021

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This paper is a critical review of in situ full-field measurements provided by digital image correlation (DIC) for inspecting and enhancing additive manufacturing (AM) processes. The principle of DIC is firstly recalled and its applicability during different AM processes systematically addressed. Relevant customisations of DIC in AM processes are highlighted regarding optical system, lighting and speckled pattern procedures. A perspective is given in view of the impact of in situ monitoring regarding AM processes based on target subjects concerning defect characterisation, evaluation of residual stresses, geometric distortions, strain measurements, numerical modelling validation and material characterisation. Finally, a case study on in situ measurements with DIC for wire and arc additive manufacturing (WAAM) is presented emphasizing opportunities, challenges and solutions.

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“…• muDIC: Pure Python toolkit, limited to 2D images (Olufsen, Andersen, & Fagerholt, 2020) but has a fully function global approach • UFreckles: Graphical Matlab code (Rethoré, 2018) working on 2D, surface and 3D images with a global approach • StrainMaster: Closed-source software for surface and 3D image correlation from LaVision • VIC3D: High-speed closed-source software for surface imaging from Correlated Solutions…”

Section: State Of the Fieldmentioning

confidence: 99%