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MultiDIC/MultiDIC: Matlab 3D Digital Image Correlation Toolbox

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

MultiDIC/MultiDIC

开源软件地址(OpenSource Url):

https://github.com/MultiDIC/MultiDIC

开源编程语言(OpenSource Language):

MATLAB 82.2%

开源软件介绍(OpenSource Introduction):

MultiDIC: a MATLAB Toolbox for Multi-View 3D Digital Image Correlation

Summary

This is the official repository associated with the paper: MultiDIC: an Open-Source Toolbox for Multi-View 3D Digital Image Correlation (DOI: 10.1109/ACCESS.2018.2843725).
MultiDIC is an open-source MATLAB toolbox by Dana Solav. Three-dimensional (stereo) Digital Image Correlation (3D-DIC) is an important technique for measuring the mechanical behavior of materials. MultiDIC was developed to allow fast calibration and data merging even for a large number of cameras, and to be easily adaptable to different experimental requirements. If you're interested in using only 2 cameras, you should check out DuoDIC. MultiDIC integrates the 2D-DIC subset-based software Ncorr with several camera calibration algorithms to reconstruct 3D surfaces from multiple stereo image pairs. Moreover, it contains algorithms for merging multiple surfaces, and for computing and visualizing 3D displacement, deformation and strain measures. High-level scripts allow users to perform 3D-DIC analyses with minimal interaction with MATLAB syntax, while proficient MATLAB users can also use stand-alone functions and data-structures to write custom scripts for specific experimental requirements. Comprehensive documentation, instruction manual, and sample data are included.
Check out this short video for a quick demonstration of MultiDIC's capabilities:

Installation

System Requirements

MultiDIC was developed and tested on 64-bit Windows 10 and has not yet been tested on other platforms.

MATLAB

MultiDIC was developed on MATLAB versions R2017a and R2017b, and has not yet been tested on prior versions.

MATLAB toolbox dependencies:

  • Image Processing Toolbox
  • Computer Vision System Toolbox
  • Statistics and Machine Learning Toolbox

Installation Instructions

To install MultiDIC simply follow these two steps:

1. Get a copy of MultiDIC

Use one of these two options:
a. Download and unzip the latest zip file.
b. Clone MultiDIC using: git clone https://github.com/MultiDIC/MultiDIC/.git.

2. Install (or add to path)

Use one of these two options:
a. In MATLAB, navigate to the unzipped MultiDIC folder, type installMultiDIC in the command window, and hit Enter.
b. In MATLAB, Add the MultiDIC folder (with subfolders) to the path and save the path definitions.

Getting started

Check out the instruction manual. It should have all the information you need to get started.

Citing

This is the official repository for:

MultiDIC: an Open-Source Toolbox for Multi-View 3D Digital Image Correlation
Dana Solav, Kevin M. Moerman, Aaron M. Jaeger, Katia Genovese, Hugh M. Herr
DOI: 10.1109/ACCESS.2018.2843725

Please cite this paper if you use the toolbox.

Contributing

If you wish to contribute code/algorithms to this project, or to propose a collaboration study, please send an email to danask (at) mit (dot) edu.

Application Highlights

These are some examples of figures obtained using MultiDIC:

Shape change and skin deformation induced by joint movement and muscle contraction

Shape change and skin deformation induced by indentation

Publications

MultiDIC has been used in the following publications:

  1. Solav, Dana, et al. "MultiDIC: An open-source toolbox for multi-view 3D digital image correlation." IEEE Access 6 (2018): 30520-30535.
  2. Solav, Dana, et al. "A framework for measuring the time-varying shape and full-field deformation of residual limbs using 3-D digital image correlation." IEEE Transactions on Biomedical Engineering 66.10 (2019): 2740-2752.
  3. Sun, Tao, et al. "Decoding of facial strains via conformable piezoelectric interfaces." Nature biomedical engineering 4.10 (2020): 954-972.
  4. Cabrera, Isaac A., et al. "Seeing the Big Picture: Improving the prosthetic design cycle using 360 3D digital image correlation." (2020).
  5. DeNise, Adam. Implementing 3D Digital Image Correlation to Study the Dynamics of Globally-Coupled Multistable Structures. Diss. The Ohio State University, 2019.
  6. Kao, Anika Rothlin, Chang Xu, and Gregory John Gerling. "Using Digital Image Correlation to Quantify Skin Deformation with Von Frey Monofilaments." IEEE Transactions on Haptics (2021).
  7. Pisonero, Javier, et al. "A Comparative Study of 2D and 3D Digital Image Correlation Approaches for the Characterization and Numerical Analysis of Composite Materials." IEEE Access 9 (2021): 160675-160687.
  8. Stereo Digital Image Correlation in MATLAB
  9. Hebert, John J. "Using Multi-Dimensional Digital Image Correlation to Measure Mechanical Properties of Additively Manufactured and Anisotropic Materials."" Diss. University of Louisiana at Lafayette, 2020.
  10. Pflüger, Jonathan, Yuting Chen, and Christian Breitsamter. "Deformation Measurements of a Full Span Model with Adaptive Elasto-Flexible Membrane Wings." STAB/DGLR Symposium. Springer, Cham, 2020.
  11. Gacek, Elizabeth, Arin M. Ellingson, and Victor H. Barocas. "In Situ Lumbar Facet Capsular Ligament Strains Due to Joint Pressure and Residual Strain." Journal of biomechanical engineering 144.6 (2022): 061007.
  12. Li, Yuanzhe, et al. "Imaging dynamic three-dimensional traction stresses." Science advances 8.11 (2022): eabm0984.
  13. Jung, Yei Hwan, et al. "A wireless haptic interface for programmable patterns of touch across large areas of the skin." Nature Electronics (2022): 1-12.
  14. Álvarez-Blanco, Mario, et al. "Crack morphology in lattice-core specimens made of biopolymer via fused deposition modelling." Procedia Structural Integrity 39 (2022): 379-386.

License

MultiDIC is provided under the Apache-2.0 license. The license file is found on the GitHub repository.




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