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Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review

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TLDR
In this article, a review of the 2D digital image correlation (2D DIC) technique for displacement field measurement and strain field estimation is presented, and detailed analyses of the measurement accuracy considering the influences of both experimental conditions and algorithm details are provided.
Abstract
As a practical and effective tool for quantitative in-plane deformation measurement of a planar object surface, two-dimensional digital image correlation (2D DIC) is now widely accepted and commonly used in the field of experimental mechanics. It directly provides full-field displacements to sub-pixel accuracy and full-field strains by comparing the digital images of a test object surface acquired before and after deformation. In this review, methodologies of the 2D DIC technique for displacement field measurement and strain field estimation are systematically reviewed and discussed. Detailed analyses of the measurement accuracy considering the influences of both experimental conditions and algorithm details are provided. Measures for achieving high accuracy deformation measurement using the 2D DIC technique are also recommended. Since microscale and nanoscale deformation measurement can easily be realized by combining the 2D DIC technique with high-spatial-resolution microscopes, the 2D DIC technique should find more applications in broad areas.

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Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

TL;DR: An overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment and some of the key challenges that persist toward the goal of automated vision-based civil infrastructure and monitoring are presented.
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Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation

TL;DR: In this article, a simple and easy-to-calculate yet effective global parameter, called mean intensity gradient, is proposed for quality assessment of the speckle patterns used in DIC.
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Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations

TL;DR: In this article, a Gauss-Newton-based digital image correlation (DIC) method was proposed to eliminate the redundant computations involved in conventional DIC method using forward additive matching strategy and classic Newton-Raphson (FA-NR) algorithm without sacrificing its sub-pixel registration accuracy.
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Computer vision for SHM of civil infrastructure: From dynamic response measurement to damage detection – A review

TL;DR: This review paper is intended to summarize the collective experience that the research community has gained from the recent development and validation of the vision-based sensors for structural dynamic response measurement and SHM.
References
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Journal ArticleDOI

Surfaces generated by moving least squares methods

TL;DR: In this article, an analysis of moving least squares (m.l.s.) methods for smoothing and interpolating scattered data is presented, in particular theorems concerning the smoothness of interpolants and the description of m. l.s. processes as projection methods.
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Digital Particle Image Velocimetry

TL;DR: In this article, the directional ambiguity associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images, and the recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.
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Digital Imaging Techniques In Experimental Stress Analysis

TL;DR: In this paper, the surface displacement components in laser speckle metrology were measured using a digital image scanner interfaced to a computer. Butt et al. used a boundary integral equation method to calculate surface traction in the contour.
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Digital image correlation using Newton-Raphson method of partial differential correction

TL;DR: In this paper, the authors developed and limited experimental verification of a method which can determine displacements and gradients using the Newton-Raphson method of partial corrections, which was shown to be accurate in determining displacement and certain gradients, while using significantly less CPU time than the current coarse-fine search method.
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