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.     

A fast digital image correlation method for deformation measurement

Fast and high-accuracy deformation analysis using digital image correlation (DIC) has been increasingly important and highly demanded in recent years. In literature, the DIC method using the Newton-Rapshon (NR) algorithm has been considered as a gold standard for accurate sub-pixel displacement tracking, as it is insensitive to the relative deformation and rotation of the target subset and thus provides highest sub-pixel registration accuracy and widest applicability. A significant drawback of conventional NR-algorithm-based DIC method, however, is its extremely huge computational expense. In this paper, a fast DIC method is proposed deformation measurement by effectively eliminating the repeating redundant calculations involved in the conventional NR-algorithm-based DIC method. Specifically, a reliability-guided displacement scanning strategy is employed to avoid time-consuming integer-pixel displacement searching for each calculation point, and a pre-computed global interpolation coefficient look-up table is utilized to entirely eliminate repetitive interpolation calculation at sub-pixel locations. With these two approaches, the proposed fast DIC method substantially increases the calculation efficiency of the traditional NR-algorithm-based DIC method. The performance of proposed fast DIC method is carefully tested on real experimental images using various calculation parameters. Results reveal that the computational speed of the present fast DIC is about 120-200 times faster than that of the traditional method, without any loss of its measurement accuracy     

Assessment of speckle-pattern quality in digital image correlation based on gray intensity and speckle morphology

In digital image correlation (DIC), speckle patterns are generated on the surface of a specimen to resolve uniqueness issues. Thus, speckle patterns significantly affect the accuracy of image correlation. To assess the quality of speckle patterns, the standard deviation of gray intensities within each speckle (SDGIS) is introduced as a new metric. On the basis of the cumulative distribution of SDGIS, speckle-pattern quality measurement (ρ) is proposed, which integrates the features of gray intensity and speckle morphology. Twelve speckle patterns are generated by changing the spraying time and nozzle sizes of an airbrush because these are associated with the speckle volume fraction and speckle size, respectively. In addition, three displacement fields are used to investigate the effects of speckle patterns on the accuracy of the DIC results. For the 12 speckle images associated with the three displacement fields, the correlation results demonstrate that the proposed speckle-pattern quality measurement is inversely proportional to the averaged error of the subset method. This is statistically confirmed by evaluating the correlation coefficient and p-value. Furthermore, the error of the subset method is more affected by speckle patterns than the subset size when the subset size is sufficiently large.     

Calibration and correction of lens distortion for two-dimensional digital speckle correlation measurement

Lens distortion practically presents in optical imaging system using in two-dimensional digital speckle correlation measurement (2D-DSCM) system, and gives rise to additional errors in the displacement and strain measurement. Camera calibration procedure is performed to obtain the coefficients of radial distortion and tangential distortion. The corrected displacement fields can be calculated using the distortion coefficient. The influence of distortion on displacement and strain measurement errors in experiment is further discussed. The three-point bending test result shows that the camera lens calibration method can effectively eliminate the effect of lens distortion and improve displacement and strain measurement accuracy.     

Measuring thickness change of transparent plate by electronic speckle pattern interferometry and digital image correlation

The thickness change of transparent plates was measured by electronic speckle pattern interferometry (ESPI) method and digital image correlation (DIC) method. An out-of-plane ESPI system was developed based on the Michelson interferometer, and a new thickness measurement method was designed, which is on the basis of Snell's law of refraction and DIC. The main principles and experimental procedures of these two methods were presented. The thickness change of polymethyl specimens under uniaxial tensile loading were measured by the optical techniques and compared with each other. The results reveal that the data obtained with DIC method achieve better linearity than ESPI.     

A space-time approach in digital image correlation: Movie-DIC

A new method is proposed to estimate arbitrary velocity fields from a time series of images acquired by a single camera. This approach, here focused on a single spatial plus a time dimension, is specialized to the decomposition of the velocity field over rectangular shaped (finite-element) bilinear shape functions. It is therefore assumed that the velocity field is essentially aligned along one direction. The use of a time sequence over which the velocity is assumed to have a smooth temporal change allows one to use elements whose spatial extension is much smaller than in traditional digital image correlation based on successive image pairs. This method is first qualified by using synthetic numerical test cases, and then applied to a dynamic tensile test performed on a tantalum specimen. Improvements with respect to classical digital image correlation techniques are observed in terms of spatial resolution.     

A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.     

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.     

基于单幅数字散斑投影及图像相关的离面振动测量

采用单幅数字散斑图投影及高速数字图像采集技术,研究了动态离面位移的测量。采用商用液晶投影仪将计算机产生的模拟散斑图投影到待测动态变形物体表面,由高速数字图像采集设备摄取并保存变形散斑图,采用时间序列数字图像相关软件计算出物体表面各点随时间变化的离面位移。这种方法用于振动分析时不仅可以获得振型分布,而且还可以获得各点的振幅值。与现有的激光频闪照相测振及激光多普勒测振等方法相比,具有光学系统简单,可全场定量测量。悬臂梁振动实验结果证实了该方法的有效性。     

Full-field digital image correlation with Kriging regression

A full-field Digital Image Correlation (DIC) method with integrated Kriging regression is presented in this article. The displacement field is formulated as a best linear unbiased model that includes the correlations between all the locations in the Region of Interest (RoI). A global error factor is employed to extend conventional Kriging interpolation to quantify displacement errors of the control points. An updating strategy for the self-adaptive control grid is developed on the basis of the Mean Squared Error (MSE) determined from the Kriging model. Kriging DIC is shown to outperform several other full-field DIC methods when using open-access experimental data. Numerical examples are used to demonstrate the robustness of Kriging DIC to different choices of initial control points and to speckle pattern variability. Finally Kriging DIC is tested on an experimental example.     

Two-step digital image correlation for micro-region measurement

A method of two-step digital image correlation is well developed with more stable and reliable calculating technology, which consists of a simple searching method and an iterative correlation method. This new method can not only improve the calculating speed and the measuring accuracy, but also simplify the process of the experiment. In order to further increase the sensitivity of the technique, the sub-pixel reconstruction is performed in sub-image by utilizing the higher precision calculation of bicubic spline interpolation value method, and the accuracy of displacement is extended to better than 0.01 pixel; the strain resolution is limited to less than 0.0002 in micro-region. The above method is applied to quantify the micro-deformation of bimaterial sample and coating sample. The experimental results show that the method of two-step digital image correlation is a potential boon to investigations at extremely small-size scales.     

High-efficiency and high-accuracy digital image correlation for three-dimensional measurement

The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the three-dimensional DIC (3D-DIC), these issues are much more serious. First, there are two cameras employed which increases the computational amount several times. Second, because of the differences in view angles, the must-do stereo correspondence between the left and right images is equivalently a non-uniform deformation, and cannot be weakened by increasing the sampling frequency of digital cameras. This work mainly focuses on the efficiency and accuracy of 3D-DIC. The inverse compositional Gauss–Newton algorithm (IC-GN²) with the second-order shape function is firstly proposed. Because it contains the second-order displacement gradient terms, the measurement accuracy for the non-uniform deformation thus can be improved significantly, which is typically one order higher than the first-order shape function combined with the IC-GN algorithm (IC-GN¹), and 2 times faster than the second-order shape function combined with the forward additive Gauss–Newton algorithm (FA-GN²). Then, based on the features of the IC-GN¹ and IC-GN² algorithms, a high-efficiency and high-accuracy measurement strategy for 3D-DIC is proposed in the end.     

Application of iteration and finite element smoothing technique for displacement and strain measurement of digital speckle correlation

In this paper, an improved method for measuring displacement in digital speckle correlation technology, which is based on an iterative and spatial-gradient algorithm, is developed. After obtaining full-field displacement, both finite element method and 2D generalized cross-validation (GCV) algorithm are adopted for smoothing the displacement field, and then the strain field can be obtained from the smoothed displacement field. The method is estimated by simulated speckle patterns and three-point bending experiment. All the results show the improved method can obtain a reasonable estimation of displacement and strain fields in digital speckle correlation method.     

A weighting window applied to the digital image correlation method

In the digital image correlation method, two steps are used to calculate the displacements of tested images. The first step is to locate the integer-pixel displacement, and the next one is to compute the sub-pixel displacement based on the first step. The benefit from the computation method for the integer-pixel displacement is that its results directly affect the displacement accuracy of each point in tested images. In this paper, a new method is developed to calculate the displacement fields between two images taken before and after deformation of an object. A new correlation function with a weighting factor related to the position of each point in the image is taken into account. The analysis and experimental results confirm the validity of the new method. In addition, the calculation results from our method have more accuracy than that of the traditional one.     

Measuring velocity of speckle fields with digital speckle pattern interferometry

We investigate a digital method for detecting the velocity of a diffusing object. The technique is based on Digital Speckle Pattern Interferometry (DSPI). A set of reference fringes is generated externally through the reference beam in a digital interferometer. As the object moves, subsequent frames are acquired and subtracted according to the normal DSPI procedure and stored. By means of the theory of first order speckle statistics applied to speckle intensity correlation, we relate the visibility variations in the reference fringes with the object velocity. Thus, by measuring the fringe visibility variation in the resulting DSPI stored frames the mean object velocity can be obtained. The theoretical results are experimentally verified.     

An improved method for shape measurement using two-dimensional digital image correlation

Shape measurement is a significant application of digital image correlation (DIC). An improved method that combines a rotatable plane mirror is proposed to measure the shape of an immovable object. In this method, two images, one before and the other after rotating the plane mirror, are obtained and then in-plane translation which related to the shape of the detected object can be calculated by the use of two-dimensional digital image correlation (2D DIC). The relationship between the in-plane translation and the shape of the object is described. Experimental results show that the proposed method is feasible for shape and distance measurement with high accuracy.