Digital image correlation with gray gradient constraints: Application to spatially variant speckle images

As a carrier of local deformation information, speckle pattern inside a subset is usually crucial for surface displacement acquisition based upon a digital image correlation (DIC) method, since both accuracy and precision of DIC method are closely related to the amount of speckle information in a subset. Although some comprehensive theoretical frameworks have been developed to estimate the quality of local speckle patterns, it is still a great challenge how to effectively integrate the subset speckle information into the well-developed correlation criteria used for DIC. By means of a well-designed square window function, we here propose the concept of continuous subset in order to modulate subset size in a continuously derivable manner. Afterwards, we further develop a new constrained zero-normalized sum-of-squared differences (CZNSSD) criterion and construct the corresponding iterative algorithm, based on which the subset size involved can be automatically determined according to the necessary amount of speckle information. Numerical results of synthetic speckle images indicate that the set of algorithm can enhance the accuracy and precision of displacement measurement, especially for spatially variant speckle images.     

Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns

This paper discusses the effect of pre-processing image blurring on the uncertainty of two-dimensional digital image correlation (DIC) measurements for the specific case of numerically-designed speckle patterns having particles with well-defined and consistent shape, size and spacing. Such patterns are more suitable for large measurement surfaces on large-scale specimens than traditional spray-painted random patterns without well-defined particles. The methodology consists of numerical simulations where Gaussian digital filters with varying standard deviation are applied to a reference speckle pattern. To simplify the pattern application process for large areas and increase contrast to reduce measurement uncertainty, the speckle shape, mean size and on-center spacing were selected to be representative of numerically-designed patterns that can be applied on large surfaces through different techniques (e.g., spray-painting through stencils). Such “designer patterns” are characterized by well-defined regions of non-zero frequency content and non-zero peaks, and are fundamentally different from typical spray-painted patterns whose frequency content exhibits near-zero peaks. The effect of blurring filters is examined for constant, linear, quadratic and cubic displacement fields. Maximum strains between ±250 and ±20,000 µε are simulated, thus covering a relevant range for structural materials subjected to service and ultimate stresses. The robustness of the simulation procedure is verified experimentally using a physical speckle pattern subjected to constant displacements. The stability of the relation between standard deviation of the Gaussian filter and measurement uncertainty is assessed for linear displacement fields at varying image noise levels, subset size, and frequency content of the speckle pattern. It is shown that bias error as well as measurement uncertainty are minimized through Gaussian pre-filtering. This finding does not apply to typical spray-painted patterns without well-defined particles, for which image blurring is only beneficial in reducing bias errors.     

Quality assessment of speckle patterns for digital image correlation

Digital image correlation (DIC) is an optical–numerical full-field displacement measuring technique, which is nowadays widely used in the domain of experimental mechanics. The technique is based on a comparison between pictures taken during loading of an object. For an optimal use of the method, the object of interest has to be covered with painted speckles. In the present paper, a comparison is made between three different speckle patterns originated by the same reference speckle pattern. A method is presented for the determination of the speckle size distribution of the speckle patterns, using image morphology. The images of the speckle patterns are numerically deformed based on a finite element simulation. Subsequently, the displacements are measured with DIC-software and compared to the imposed ones. It is shown that the size of the speckles combined with the size of the used pixel subset clearly influences the accuracy of the measured displacements.     

Evaluation of the quality of a speckle pattern in the digital image correlation method by mean subset fluctuation

The quality of the speckle pattern used in digital image correlation is studied in this paper using a parameter called mean subset fluctuation. A numerical translation test is performed on four speckle patterns captured from actual experiments. The translated images are analyzed and the results show that the mean bias error of the calculated displacement is linear with the value of the mean subset fluctuation. The results from the numerical calculation illustrate that speckle size and density have an influence on the quality of speckle pattern.     

Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors

The performance of digital image correlation (DIC) is influenced by the quality of speckle patterns significantly. Thus, it is crucial to present a valid and practical method to assess the quality of speckle patterns. However, existing assessment methods either lack a solid theoretical foundation or fail to consider the errors due to interpolation. In this work, it is proposed to assess the quality of speckle patterns by estimating the root mean square error (RMSE) of DIC, which is the square root of the sum of square of systematic error and random error. Two performance evaluation parameters, respectively the maximum and the quadratic mean of RMSE, are proposed to characterize the total error. An efficient algorithm is developed to estimate these parameters, and the correctness of this algorithm is verified by numerical experiments for both 1 dimensional signal and actual speckle images. The influences of correlation criterion, shape function order, and sub-pixel registration algorithm are briefly discussed. Compared to existing methods, method presented by this paper is more valid due to the consideration of both measurement accuracy and precision.     

Study of optimal subset size in digital image correlation of speckle pattern images

This paper investigates the effect of subset size, associated with image pattern quality and subset displacement functions, on the accuracy of deformation measurements by digital image correlation(DIC). A concept of subset entropy is introduced in this work to quantify the subset image pattern quality for DIC analysis and its effectiveness was demonstrated by experimental studies. By employing white-light images with almost uniform subset entropy and first-order displacement functions, the effect of subset size on DIC analysis was investigated for the deformation cases of translation, uniform deformation, and simulated quadratic deformation, respectively. The results show that the chosen subset size must be large enough for precise displacement measurements when subset displacement functions match underlying actual deformation. On the other hand, optimal subset size in DIC for nonhomgeneous deformation measurements appears as a result of a tradeoff between the influence of random errors and systematic errors.     

Use of rigid-body motion for the investigation and estimation of the measurement errors related to digital image correlation technique

The aim of this work is to investigate the sources of errors related to digital image correlation (DIC) technique applied to strain measurements. The knowledge of such information is important before the measured kinematic fields can be exploited. After recalling the principle of DIC, some sources of errors related to this technique are listed. Both numerical and experimental tests, based on rigid-body motion, are proposed. These tests are simple and easy-to-implement. They permit to quickly assess the errors related to lighting, the optical lens (distortion), the CCD sensor, the out-of-plane displacement, the speckle pattern, the grid pitch, the size of the subset and the correlation algorithm. The errors sources that cannot be uncoupled were estimated by amplifying their contribution to the global error. The obtained results permit to address a classification of the error related to the used equipment. The paper ends by some suggestions proposed in order to minimize the errors.     

基于一阶及二阶灰度梯度的散斑图质量评价方法

散斑图质量对数字图像相关(DIC)方法的测量精度具有重要的影响。以平均灰度梯度这一传统的散斑图质量评价参数作为基础,提出了一种新的评价参数——平均一阶及二阶灰度梯度商,该参数同时考虑了一阶和二阶灰度梯度。从整体上来说,一阶灰度梯度的曲面比较光滑,而一阶及二阶灰度梯度商的曲面比较粗糙。采用Zhou等人提出的方法制作了80张模拟散斑图,对这些模拟散斑图的传统参数和提出参数进行了计算。结果表明:当散斑半径相同时,随着散斑数量的增加,两种参数均先增加,后减小;当散斑数量一定时,二者均有一个峰值;散斑半径越大,提出参数的峰值越大,而传统参数的峰值越小。对提出参数的峰值所对应的4张散斑图进行了多次连续平动,并使用DIC方法测量了测点的水平位移。结果表明,在提出参数越大的散斑图上测点的水平位移误差越小,在一定程度上验证了提出参数的正确性。     

Speckle pattern quality assessment for digital image correlation

To perform digital image correlation (DIC), each image is divided into groups of pixels known as subsets or interrogation cells. Larger interrogation cells allow greater strain precision but reduce the spatial resolution of the data field. As such the spatial resolution and measurement precision of DIC are limited by the resolution of the image. In the paper the relationship between the size and density of speckles within a pattern is presented, identifying that the physical properties of a pattern have a large influence on the measurement precision which can be obtained. These physical properties are often overlooked by pattern assessment criteria which focus on the global image information content. To address this, a robust morphological methodology using edge detection is devised to evaluate the physical properties of different speckle patterns with image resolutions from 23 to 705 pixels/mm. Trends predicted from the pattern property analysis are assessed against simulated deformations identifying how small changes to the application method can result in large changes in measurement precision. An example of the methodology is included to demonstrate that the pattern properties derived from the analysis can be used to indicate pattern quality and hence minimise DIC measurement errors. Experiments are described that were conducted to validate the findings of morphological assessment and the error analysis.     

A general strategy of in-situ warpage characterization for solder attached packages with digital image correlation method

Recently, 3-D Digital Image Correlation (DIC) is widely applied to the reliability analysis of electronic packages, which particularly characterizes the in-situ deformation of ball grid array (BGA) packages. During the image correlation procedure, many parameters influence the accuracy and data integrity of measurement result. Facet (subset) size is the principal parameter and has been studied with much effort. However, the solder balls, which are built on the substrate surface, make the scenario different with the conventional 3-D DIC experiment for the planar samples. The undulant surface generates more obstacles for the successful image correlation. In order to summarize an effective solution of 3-D DIC measurement method for solder balls attached packages, camera angle, facet size and facet step are studied with different BGA packages and different stereoscopic camera systems to achieve the best correlation quality. Also, a novel surface treatment method is introduced to guarantee the surface speckles are generated uniformly on the fluctuant surface.     

Digital image correlation involves an inverse problem: A regularization scheme based on subset size constraint

Digital image correlation (DIC) is essentially implicated in a class of inverse problem. Here, a regularization scheme is developed for the subset-based DIC technique to effectively inhibit potential ill-posedness that likely arises in actual deformation calculations and hence enhance numerical stability, accuracy and precision of correlation measurement. With the aid of a parameterized two-dimensional Butterworth window, a regularized subpixel registration strategy is established, in which the amount of speckle information introduced to correlation calculations may be weighted through equivalent subset size constraint. The optimal regularization parameter associated with each individual sampling point is determined in a self-adaptive way by numerically investigating the curve of 2-norm condition number of coefficient matrix versus the corresponding equivalent subset size, based on which the regularized solution can eventually be obtained. Numerical results deriving from both synthetic speckle images and actual experimental images demonstrate the feasibility and effectiveness of the set of newly-proposed regularized DIC algorithms.     

Development of microscale pattern for digital image correlation up to 1400 °C

Speckle patterns to be used for digital image correlation (DIC) at the micrometer level up to 1400 °C were fabricated by several methods. The quality of the patterns before and after heating was evaluated in terms of the mean intensity gradient (MIG) and the speckle size distribution. The displacement accuracy in simulative translation of images showed that the MIG alone was not enough to evaluate the pattern properties; a large MIG, an even speckle size distribution, and a wide speckle size range pattern were required for a good DIC. The reaction between the patterning material and substrate, the cracking of speckles, and the plastic flow of patterning material may cause changes in the pattern morphology at high temperature. Two patterning methods, spraying a mixture of ceramics powder and binder by a fine-nozzle air brush and abrading a polished surface, yielded a small pattern with high MIG values and even size distributions that was stable at 1400 °C. The potential of the fabricated patterns was shown by measuring the coefficient of thermal expansion of polycrystalline Al₂O₃ from 800 °C to 1400 °C.     

The study of fractal correlation method in the displacement measurement and its application

The classical digital speckle, or digital image, correlation method of deformation measurement is based on gray level correlation between unformed and deformed digital images. The pattern of artificial random speckles and the natural textures on some object's surfaces have fractal characteristics, and their fractal dimensions represent both gray and morph information. Furthermore, the fractal dimensions are stable feature parameters of the patterns. The digitized images of the patterns are confirmed to be also fractals. By this fact, a new method of displacement measurement is developed in the paper, based on the fractal dimensions correlation. The in-plane displacement fields of a body can be acquired. In order to verify the validity of the new method, an experiment has been designed and the results have been compared with those obtained from the classical digital image correlation method. The validity of the new method is not less than that of classical method. Further discussions about the traits and the developing vista of the method are given at the end.     

On the use of the digital image correlation method for heterogeneous deformation measurement of porous solids

In this paper, several crucial issues arising from the application of the digital image correlation (DIC) method to the measurement of heterogeneous deformation of porous solids are discussed. To handle samples with complex geometry, the performance of the two commonly employed DIC methods, namely the subset-based DIC and the finite-element based DIC methods are first evaluated and compared. A combined DIC approach and an adaptive DIC approach suitable for samples with discontinuities/holes are then proposed. Aluminum plates with circular holes subject to compressive loading are employed to evaluate the accuracy of the proposed methods. It has been found that in addition to other factors such as the number of pixels and speckle size, the orientation of the camera lens also plays an important role on the measurement accuracy. A calibration method for the adjustment of camera orientation is proposed, which leads to a good agreement between the experimentally measured displacements and finite element simulation results. Another finding of the presented work is that for relatively stiff specimens, the deformation of the loading system itself must be considered in order to obtain an accurate displacement.     

数字散斑亚像素小角位移测量的曲面拟合法

与传统测量方法相比,数字散斑相关法由于其目标特征单元网格划分的灵活性,能够更好地满足不同场合小角位移的测量需求。针对该方法亚像素小角位移测量的曲面拟合参数选择问题,研究了亚像素测量图像小角旋转前后的九点二次曲面拟合法,并根据计算机生成模拟散斑进行模拟实验分析,得到最佳误差效率优化条件下的曲面拟合法求解亚像素小角位移的最佳散斑尺寸3.5 pixel、计算窗口尺寸41×41 pixel和拟合窗口尺寸3×3 pixel。实验验证了上述测量参数的有效性,为进一步的曲面拟合法数字散斑成像角位移测量提供参考。     

斜光轴面内位移测量的数字散斑相关法研究

以工程环境中远距离位移和位移场的光学测量为研究课题,分析了远距离斜光轴成像时,像模糊和成像位置变化对白光数字散斑相关方法产生的影响,给出了这两种影响的误差理论计算公式。提出使用参考测量技术克服斜光轴成像位置变化带来影响,给出一种新的远距离斜光轴高精度测量面内位移的方法,在2～50m处作静载挠度测量,其最大相对误差小于1％,测量精度在实验室环境和工程测量环境中都得到了验证。该方法无需共轴光路的测量环境要求,特别适用于桥梁、高速公路立交桥的静载挠度测量等工程应用。使用高速图像采集卡,该方法可应用于斜光轴动态位移测量,拓展了数字散斑相关方法的应用范围。     

Assessment of measuring errors in DIC using deformation fields generated by plastic FEA

In this article, systematic errors that arise from different implementations of digital image correlation (DIC) techniques are analyzed. In particular, we investigate the influence of the adopted correlation function, the interpolation order, the shape function and the subset size on the derived displacements. These errors are estimated using numerically deformed images that were obtained by imposing finite element (FE) displacement fields on an undeformed image yielding plastic deformation of the specimen. This FE procedure simulates realistic experimental heterogeneous deformations at various load steps. It is shown that DIC is able to reproduce these displacements up to a satisfactory level if conscious choices in the above-mentioned implementations are made.     

Axially symmetrical stresses measurement in the cylindrical tube using DIC with hole-drilling

In this paper, a new method combining the digital image correlation (DIC) with the hole-drilling technology to characterize the axially symmetrical stresses of the cylindrical tube is developed. First, the theoretical expressions of the axially symmetrical stresses in the cylindrical tube are derived based on the displacement or strain fields before and after hole-drilling. Second, the release of the axially symmetrical stresses for the cylindrical tube caused by hole-drilling is simulated by the finite element method (FEM), which indicates that the axially symmetrical stresses of the cylindrical tube calculated by the cylindrical solution is more accuracy than that for traditionally planar solution. Finally, both the speckle image information and the displacement field of the cylindrical tube before and after hole-drilling are extracted by combining the DIC with the hole-drilling technology, then the axially symmetrical loading induced stresses of the cylindrical tube are obtained, which agree well with the results from the strain gauge method.     

双目视觉DIC测量系统的离面位移测量精度

采用离面位移测量精度达到10 nm~20 nm的电子散斑干涉测量系统验证了双目视觉数字散斑相关测量系统的离面位移测量精度。分别用电子散斑干涉测量系统和双目视觉数字散斑相关测量系统同时测量了平板离面位移,并对所测量的位移最大值进行了分析处理及比较。结果表明,双目视觉数字散斑相关测量系统的物体离面位移分布云图与电子散斑干涉测量系统的结果基本相同,且两者位移均方根相差为2.76 m~3.56 m,相对误差为4.59%~7.60%。因此,当被测量物体的离面位移大于4 m时,双目视觉Q400测量系统精度可达到电子散斑干涉测量系统的精度。     

Digital image correlation using iterative least squares and pointwise least squares for displacement field and strain field measurements

Digital image correlation (DIC) method using iterative least squares algorithm (ILS) for displacement field measurement and pointwise least squares algorithm (PLS) for strain field measurement is proposed in this paper. A more general and practical intensity change model is employed with consideration of the linear intensity change of the deformed image, followed by an iterative least squares algorithm for calculating displacement field with sub-pixel accuracy. The concept of correlation function is not used in the ILS method, even though we prove that the algorithm is actually equivalent to the optimization of the sum of squared difference correlation function using improved Newton–Raphson method. Besides, different from the conventional strain estimation approaches based on smoothing the displacement fields first and followed by differentiation of the smoothed displacement fields, a simple yet effective PLS algorithm is proposed for extracting strain fields from the computed displacement fields. The effectiveness and accuracy of the proposed techniques is verified through numerical simulation experiments. A practical application of the algorithms to residual plastic deformation field measurement of GH4169 alloy subjected to tensile fatigue is also presented.