Digital Image Correlation for discontinuous displacement measurement using subset segmentation (original) (raw)
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Reconstruction of strain and displacement fields from surface images of materials and structures in the presence of discontinuities is a challenging task. Digital Image Correlation (DIC) – a commonly used technique to reconstruct displacement and strain fields when deformation is continuous – fails in the presence of discontinuities, including cracks and crevices. This paper presents a novel and entirely automated technique, Discontinuous Digital Image Correlation (DDIC), to reconstruct displacement and strain fields with high accuracy from images when deformation is either continuous or discontinuous. The technique is based on introducing additional parameters that characterize the discon-tinuity: the direction of the tangent to the discontinuity line and the corresponding Burgers vectors which express the difference in displacements at the opposite sides of the discon-tinuity line. The proposed technique is validated using synthetic images as well as images obtained from laboratory experiments. The results show that DDIC is able to reconstruct the displacement fields around discontinuities with a subpixel accuracy close to 1=100th of a pixel with a suitable surface pattern. It is also able to recover the size and angle of the discontinuity.
Discontinuous and Pattern Matching algorithm to measure deformation having discontinuities
Engineering Applications of Artificial Intelligence, 2019
Remote deformation monitoring with high accuracy is a challenging task. The technique of Digital Image Correction (DIC) is commonly used to measure remote deformation using images and provides high subpixel accuracy. However, DIC fails if deformation is non-continuous, which is a regularly occurring scenario in deformable solids due to the presence of discontinuities such as cracks and crevices. To overcome the limitation posed by DIC, a novel Discontinuous and Pattern Matching (DPM) algorithm is proposed in this study. Initially DPM algorithm demarcates the area where DIC fails by using the results of DIC. Later, DPM algorithm utilizes the features of pattern matching and embeds discontinuity in DIC to measure deformation in the demarcated areas where DIC failed. The performance of the proposed DPM algorithm is evaluated using two different experiments involving different types of discontinuities. The accuracy achieved in evaluation is higher than the normally required one-tenth of a pixel and the average absolute errors remained in the range of 0.02 to 0.07 pixels. The results are compared with another state-of-the-art DIC and pattern matching based technique and comparative analysis show that the proposed DPM algorithm improved the accuracy of deformation measurement in the range of 0.02 to 0.1 pixels depending on different scenarios.
Digital image correlation (DIC) is a well-known contact-less technique offering highly accurate full-field deformation measurement using grayscale images. The practical implementation of DIC is still facing many challenges, especially limitations of accuracy in measuring small displacement gradients for solids in geosciences and biomedi-cal engineering. In this paper, we introduce a novel approach in which color images are employed to enhance the performance of DIC. A complete framework for Color DIC has been proposed and tested. The results show that Color DIC performs significantly better than grayscale DIC for measurement of small strains by a factor of 2.
Contrast Media & Molecular Imaging
The measurement of strain using some contact techniques has some drawbacks like less accuracy and it takes larger computation time for finding each location of subpixels. Thus, a faster noncontact Digital Image Correlation (DIC) mechanism is utilized along with the traditional techniques to measure the strain. The Newton-Raphson (NR) technique is considered to be an accepted mechanism for accurate tracking of different intensity relocation. Generally, the issue regarding the DIC mechanism is its computational cost. In this paper, an interpolation technique is utilized to accomplish a high precision rate and faster image correlation; thereby it reduces the computation time required for finding the matched pixel and viably handles the rehashing relationship process. Hence, the proposed mechanism provides better efficiency along with a reduced number of iterations required for finding the identity. The number of iterations can be reduced using the Sum of Square of Subset Intensity Grad...
Reconstruction of displacement and strain fields in geomechanical structures from surface images is a challenging task. Digital Image Correlation (DIC) is a well known technique to achieve these tasks if deformation is continuous but it fails in the presence of discontinuities. This paper investigates the application of the DIC technique to displacement and strain field reconstruction in the presence of discontinuities, and presents a post-processing algorithm that leverages the convergence results in DIC to reconstruct displacement and strain fields around discontinuities with high accuracy. The proposed algorithm uses the results obtained from DIC and concentrates on the area where DIC fails. Pattern matching is conducted on the area around the discontinuities and associated displacement is found for each pixel. The proposed algorithm is tested using two different discontinuity scenarios: dislocation and fracture in structures. The results show that the proposed algorithm successfully reconstructs the displacement and strain fields to subpixel accuracy of 1/10th of a pixel.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Recently, there has been a growing interest in studying non-contact techniques for strain and displacement measurement. Within photogrammetry, Digital Image Correlation (DIC) has received particular attention thanks to the recent advances in the field of lowcost, high resolution digital cameras, computer power and memory storage. DIC is indeed an optical technique able to measure full field displacements and strain by comparing digital images of the surface of a material sample at different stages of deformation and thus can play a major role in structural monitoring applications. <br><br> For all these reasons, a free and open source 2D DIC software, named py2DIC, was developed at the Geodesy and Geomatics Division of DICEA, University of Rome <q>La Sapienza</q>. Completely written in python, the software is based on the template matching method and computes the displacement and strain fields. The potentialities of Py2DIC were evaluated by processing the ima...