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Extracting Displacement and Strain Fields from Checkerboard Images with the Localized Spectrum Analysis

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TLDR
In this article, the authors examined the case of checkerboard pattern and found that the noise level observed in displacement and strain maps is significantly lower with a checkboard than with a classic 2D grid.
Abstract
The performance of white-light full-field measurement methods strongly depends on the nature of the pattern used to mark the surface on which displacements and strains are measured. Finding optimized patterns is therefore a topical question. The aim of this study is to examine the case of the checkerboard pattern. It is first shown that this periodic pattern can be processed with a Fourier-based technique such as LSA. Experiments are then carried out to compare the noise level in displacement and strain maps obtained by processing classic 2D grid and checkerboard images. The conclusion is that the noise level observed in displacement and strain maps is significantly lower with a checkerboard than with a classic 2D grid. A notched specimen is finally tested to illustrate that very low strain levels can be measured with checkerboard patterns.

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Citations
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Journal ArticleDOI

When Deep Learning Meets Digital Image Correlation

TL;DR: This work is aimed at implementing a CNN able to retrieve displacement and strain fields from pairs of reference and deformed images of a flat speckled surface, as Digital Image Correlation does.
Journal ArticleDOI

Glare: A free and open-source software for generation and assessment of digital speckle pattern

TL;DR: Glare is a free and open-source software for generation and assessment of digital speckle pattern that realizes real-time deformed image rendering with the aid of fast initial value estimation algorithm for backward mapping and pattern pre-rendering technique, and improves the computational efficiency of sum of square of subset intensity gradients by integral image method.
Journal ArticleDOI

On the Optimal Pattern for Displacement Field Measurement: Random Speckle and DIC, or Checkerboard and LSA?

TL;DR: The main conclusion is that using checkerboards instead of random speckles leads to measurements featuring a better compromise between spatial resolution and measurement resolution.
Journal ArticleDOI

A Robust-to-Noise Deconvolution Algorithm to Enhance Displacement and Strain Maps Obtained with Local DIC and LSA

TL;DR: The present procedure can be considered as robust to noise, in the sense that off-the-shelf deconvolution algorithms do not converge in the presence of classic levels of noise observed in strain maps, which means that the proposed procedure improves the compromise between spatial resolution and measurement resolution.
Journal ArticleDOI

Glare: A free and open-source software for generation and assessment of digital speckle pattern

TL;DR: Wang et al. as mentioned in this paper presented Glare, a free and open-source software for generation and assessment of digital speckle pattern, which can generate ellipse, polygon, and Gaussian speckles, render deformed images, assess pattern quality, and present pattern recommendations.
References
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Book

Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications

TL;DR: In this paper, a comprehensive overview of image correlation for shape, motion and deformation measurements is provided. But, the authors do not discuss the effect of out-of-plane motion on 2D measurements.
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Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data

TL;DR: A signal-dependent noise model, which gives the pointwise standard-deviation of the noise as a function of the expectation of the pixel raw-data output, is composed of a Poissonian part, modeling the photon sensing, and Gaussian part, for the remaining stationary disturbances in the output data.
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Radiometric CCD camera calibration and noise estimation

TL;DR: Using physical models for charged-coupled device (CCD) video cameras and material reflectance, the variation in digitized pixel values that is due to sensor noise and scene variation is quantify.
Journal ArticleDOI

Study on subset size selection in digital image correlation for speckle patterns.

TL;DR: A theoretical model of the displacement measurement accuracy of DIC can be accurately predicted based on the variance of image noise and Sum of Square of Subset Intensity Gradients (SSSIG), which leads to a simple criterion for choosing an optimal subset size for the DIC analysis.
Journal ArticleDOI

Patch-Based Nonlocal Functional for Denoising Fluorescence Microscopy Image Sequences

TL;DR: A nonparametric regression method for denoising 3-D image sequences acquired via fluorescence microscopy and an original statistical patch-based framework for noise reduction and preservation of space-time discontinuities are presented.
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