Combining Image Compression with Digital Image Correlation

Experimental Mechanics - Digital image correlation (DIC) is a powerful experimental technique to determine displacement and strain fields. DIC methods usually require a large number of high...     

Recent Progress in Digital Image Correlation

In this paper, we report the following important progress recently made in the basic theory and practical implementation of digital image correlation (DIC) for deformation measurement. First, we answer a basic but confusing question to the users of DIC: what is a good speckle pattern for DIC? We present a simple, easy-to-compute yet effective global parameter, called mean intensity gradient, for quality assessment of the entire speckle pattern. Second, we provide an overview of various correlation criteria used in DIC for evaluating the similarity of the reference and deformed subsets, and demonstrate the equivalence of three robust and most widely used correlation criteria, i.e., a zero-mean normalized cross-correlation (ZNCC) criterion, a zero-mean normalized sum of squared difference (ZNSSD) criterion and a parametric zero-mean normalized sum of squared difference (PSSD_ab) criterion with two additional unknown parameters, which elegantly unifies these correlation criteria for subset-based pattern matching. Third, we describe an iterative least squares (ILS) algorithm for accurate subpixel motion detection, which is proved to be equivalent to the existing Newton–Raphson algorithm, but the principle and implementation of ILS algorithm is more straightforward and easier. Finally, to overcome the two limitations of existing subset-based DIC technique, we introduce a robust and generally applicable reliability-guided DIC technique, in which the calculation path is guided by the ZNCC coefficients of computed points, to determine the genuine full-field deformation of an object with complex shape.     

Digital Image Correlation and Color Cameras

Digital Image Correlation (DIC) is a well-known experimental technique. It works by constructing a (surjective) mapping of pixel intensity from reference to target image, where the mapping parameters are identified using a Least Squares approach. Because it makes use of the luminance component of the image, Digital Image Correlation is usually implemented by assuming monochrome cameras. In this work, we will discuss its implementation when color cameras are used, focusing on pitfalls and potential advantages of this solution. Since most cameras implement color acquisition using a Color Filter Array (CFA), much of the article will focus on this technology. However, we will not limit ourselves to this aspect and will show that Three-CCD cameras can provide significant advantages over both CFA and monochrome cameras.     

网格数字图像相关方法测量位移场的研究

本文将数字图像相关方法与古老的网格法相结合,给出了一种测量面内位移场的新方法——网格数字图像相关方法,实现了高精度的测量,精度可达0.02亚像素．在该方法中网格点采用圆标记点,使该方法特别适用于小线应变位移场的研测．本文运用Windows下的新的图像采集方法测量物体位移场,突破了Dos系统下对内存操作的限制,并使每一帧图像的像素数由512×512增至768×576,提高了图形的分辨率．     

Digital Image Correlation Using Stochastic Parallel-Gradient-Descent Algorithm

This article proposes a digital image correlation (DIC) method based on the stochastic parallel gradient descent (SPGD) algorithm. Stochastic parallel perturbations are imposed on deformation parameters to make the correlation coefficients converge to a global extremum; thus, this allows the final measured values of the deformation parameters to be obtained and the DIC measurement to be made. Both simulated and real data processing, including rigid body and strain deformation, show that the proposed method can achieve nearly the same accuracy as the Newton–Raphson (NR) method in most cases and higher accuracy in some cases, such as the simulated experiments of rigid body translation with and without noise. It also has a good noise-robustness. Furthermore, a series of experiments have been designed to evaluate the convergence characteristics of the proposed method, and it has been proved able to process large displacement and have a stable convergence process, good robustness, and a high convergence speed when bilinear interpolation is adopted.     

Digital Image Correlation with Self-Adaptive Gaussian Windows

A novel subpixel registration algorithm with Gaussian windows is put forward for accurate deformation measurement in digital image correlation technique. Based on speckle image quality and potential deformation states, this algorithm can automatically minimize the influence of subset sizes by self-adaptively tuning the Gaussian window shapes with the aid of a so-called weighted sum-of-squared difference correlation criterion. Numerical results of synthetic speckle images undergoing in-plane sinusoidal displacement fields demonstrate that the proposed algorithm can significantly improve displacement and strain measurement accuracy especially in the case with relatively large deformation.     

Fractal Pattern for Multiscale Digital Image Correlation

Background:

Digital Image Correlation (DIC) is based on the matching, between reference and deformed state images, of features contained in patterns that are deposited on test sample surfaces. These features are often suitable for a single scale, and there is a current lack of multiscale patterns capable of providing reliable displacement measurements over a wide range of scales.

Objective:

Here, we aim to demonstrate that a pattern based on a fractal (self-affine) surface would make a suitable pattern for multiscale DIC.

Methods:

A method to numerically generate patterns directly from a desired auto-correlation function is introduced. It is then enhanced by a Mean Intensity Gradient (MIG) improvement process based on grey level redistribution. Numerical experiments at multiple scales are performed for two different imposed displacement fields and results for one of the patterns generated are compared with those obtained for a random pattern and a Perlin noise one.

Results:

The proposed pattern is shown to lead to DIC errors comparable to those found with the two others for the first scales, but has much greater robustness. More importantly, the pattern generated here exhibits stable errors and robustness with respect to the scale whereas these two outputs become significantly degraded for the other two patterns as the scale increases.

Conclusions:

As a result, scale invariance properties of the pattern based on fractal surfaces correspond to scale invariance in DIC errors as well. This is of great interest regarding the use of such patterns in multiscale DIC.

     

Absolute Nodal Coordinates in Digital Image Correlation

A great deal of progress has been made in recent years in the field of global digital image correlation (DIC), where higher-order, element-based approaches were proposed to improve the interpolation performance and to better capture the displacement fields. In this research, another higher-order, element-based DIC procedure is introduced. Instead of the displacements, the elements’ global nodal positions and nodal position-vector gradients, defined according to the absolute nodal coordinate formulation, are used as the searched parameters of the Newton–Raphson iterative procedure. For the finite elements, the planar isoparametric plates with 24 nodal degrees of freedom are employed to ensure the gradients’ continuity among the elements. As such, the presented procedure imposes no linearization on the strain measure, and therefore indicates a natural consistency with the nonlinear continuum theory. To verify the new procedure and to show its advantages, a real large deformation experiment and several numerical tests on the computer-generated images are studied for the standard, low-order, element-based digital image correlation and the presented procedure. The results show that the proposed procedure proves to be accurate and reliable for describing the rigid-body movement and simple deformations, as well as for determining the continuous finite strain field of a real specimen.     

Cross Polarization for Improved Digital Image Correlation

Digital image correlation (DIC) is a surface deformation measurement technique for which accuracy and precision are sensitive to image quality. This work presents cross polarization, the use of orthogonal linear polarizers on light source(s) and camera(s), as an effective method for improving optical DIC measurements. The benefits of cross polarization are characterized through quantitative and statistical comparisons from two experiments: rigid body translation of a flat sample and uniaxial tension of a superelastic shape-memory alloy (SMA). In both experiments, cross polarization eliminated saturated pixels that degrade DIC measurements, and increased image contrast, which enabled higher spatial precision by using smaller subsets. Subset sizes are usually optimized for correlation confidence interval (typically with subsets of 21×21 px or larger), but can be decreased to achieve the highest possible spatial precision at the expense of increased correlation confidence intervals. Smaller subset sizes (such as 9×9 px) require better images to maintain correlation within error thresholds. By comparing DIC results from a uniaxial SMA tension test with unpolarized and cross-polarized images, we show that for 9×9 px subsets, the loss of valid DIC data points was reduced almost ten-fold with cross polarization. The only disadvantage we see to cross polarization is the decrease in specimen illumination due to transmission losses through the polarizers, which can easily be accommodated with sufficiently intense light sources. With the installation of relatively inexpensive linear polarizing filters, an optimum optical DIC setup can provide even better DIC measurements by delivering images without saturated pixels and with higher contrast for increased DIC spatial precision.     

材料交界面上连续应力分析的改进拉氏乘子法

引进材料界面的节理单元,以其刚度参数为罚参数,利用代表界面接触应力的拉氏乘子,通过迭代求解得到界面上的应力,为计算粘结在一起的不同材料交界面上的应力提供了一种非常有效的方法。     

数字图像相关分析法增量位移场测试技术

利用位移场的连续性,对亚像素位移场的算法进行了一些改进,设计了一套分步计算位移场、应变场的测量计算方法,较好地解决了数字图像相关分析法计算精度和效率.采用增量位移场叠加的方法计算大应变位移场,采用局部平面拟合的方法计算应变场.通过对高分子材料拉伸试验位移场的测量和结果标定,说明该方法具有较强的实用性和计算精度.同时,由于避免了对亚像素点的搜索,大大提高了计算效率.     

Smart Digital Image Correlation Patterns via 3D Printing

Experimental Mechanics - Digital Image Correlation (DIC) is a popular experimental technique for measuring full-field deformations in materials. Accurate motion and displacement field...     

Digital Image Correlation for Specimens with Multiple Growing Cracks

Measuring the surface displacements of specimens having multiple, growing cracks is difficult with most implementations of the digital image correlation (DIC) method. This difficulty arises from the need to exclude the cracked area from the analysis, a process that oftentimes requires significant and time-consuming user input to achieve successful results. This work presents a set of modifications to the Newton–Raphson based DIC process that allows the method to automatically analyze specimens with multiple growing cracks. The modifications combine a relatively simple crack identification process that takes advantage of the consistency of quasi-regular speckle patterns with a method to reestablish the analysis in areas segregated by the crack growth. The use of a regular dot pattern does, however, introduce a greater chance for registration error in the correlation process. A method to minimize possible registration problems is also presented. Finally, the effectiveness of the method is demonstrated using images of concrete specimens with a complex and growing crack pattern.     

Overview of High-temperature Deformation Measurement Using Digital Image Correlation

Background

Developments in digital image correlation (DIC) in the last decade have made it a practical and effective optical technique for displacement and strain measurement at high temperatures.

Objective

This overview aims to review the research progress, summarize the experience and provide valuable references for the high-temperature deformation measurement using DIC.

Methods

We comprehensively summarize challenges and recent advances in high-temperature DIC techniques.

Results

Fundamental principles of high-temperature DIC and various approaches to generate thermal environment or apply thermal loading are briefly introduced first. Then, the three primary challenges presented in performing high-temperature DIC measurements, i.e., 1). image saturation caused by intensified thermal radiation of heated sample and surrounding heating elements, 2) image contrast reduction due to surface oxidation of the heated sample and speckle pattern debonding, and 3) image distortion due to heat haze between the sample and the heating source, and corresponding countermeasures (i.e., the suppression of thermal radiation, fabrication of high-temperature speckle pattern and mitigation of heat haze) are discussed in detail. Next, typical applications of high-temperature DIC at various spatial scales are briefly described. Finally, remaining unsolved problems and future goals in high-temperature deformation measurements using DIC are also provided. 

Conclusions

We expect this review can guide to build a suitable DIC system for kinematic field measurements at high temperatures and solve the challenging problems that may be encountered during real tests.

     

散斑图像相关数字技术原理及应用

研究图像处理技术在散斑测量中的应用，提出了一种散斑图像相关数字技术，该方法引进了亚像素技术，采用重心算法计算特征斑的重心，避免了数字散斑相关法计算相关系数的繁复过程；应用位移和应变的有关公式，可以获得物体变形实验曲线，实验结果表明，该方法在工程实际现场、振动过程以及变形测量的自动化等方面有着广泛的应用潜力，从而为光测力学拓展应用领域、实现自动化测量展现了新的前景。     

Mirror-assisted Multi-view Digital Image Correlation with Improved Spatial Resolution

Experimental Mechanics - Accurate measurements of panoramic/dual-surface kinematic fields are essential to elastoplastic mechanics for the determination of true stress-strain curves,...     

橡胶材料弹性模量数字图像相关测定法

利用数字图像相关方法测量了小应变下柔性橡胶的弹性模量.用CCD相机记录单轴压缩实验中圆柱体橡胶试样表面人工散斑图像,作为数字图像相关测量技术中的变形信息载体.分析了镜头畸变对位移测量的影响,运用数字图像相关法得出小应变范围内像胶的应力应变曲线,计算出橡胶的弹性模量.并与采用千分表所得到的结果进行了比较,两者符合较好.实...     

Implementation of Convergence in Adaptive Global Digital Image Correlation

In FE based global digital image correlation (DIC) a finite element mesh is used to describe the deformation of the region of interest (ROI). However, the identification of an optimal mesh is a difficult problem and is often obtained by using “mechanical” pre-knowledge of the solution. In Finite Element Analysis (FEA) an optimal mesh can be found without any pre-knowledge of the solution by using mesh adaptivity, where an initial (non optimal) mesh is refined until the optimal solution is obtained. Refinement of the mesh can be based on error and/or convergence estimators. Despite the fundamental differences between FEA and DIC, in the present article the convergence procedure is successfully used in a recently published global FE based DIC method. In the used global DIC method elements can receive higher order shape functions, also known as p-elements. Using the aforementioned algorithm, also called p-DIC, refinement to a non-uniform higher order mesh is possible. Using the non-uniform mesh, an optimal mesh can be obtained for each section of the ROI. The presented study shows that a convergence scheme can be used to automatically control the mesh refinement in a global DIC approach. The convergence boundary, in percentage, is a more intuitive boundary than the absolute error boundary used in the original p-DIC approach. The procedure is validated using numerical examples and the robustness to experimental variables is investigated. Finally, the complete procedure is tested against a wide range of practical examples.