Improved Digital Image Correlation method

Mudassar, Asloob A.; Butt, Saira

doi:10.1016/j.optlaseng.2015.10.002

Cited by 24 publications

(11 citation statements)

References 47 publications

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“…The process was slightly different from that of I-DIC. [12][13][14] In DIC, the formed reference and test images are correlated, the correlation image contains over peak correlation or autocorrelation, the height of the peak provides a similarity of magnitude between two sets of images, and the location provides the peak and displacement of the test image. The dataset was in the form of images.…”

Section: Methodsmentioning

confidence: 99%

“…The second and third steps were the same as that in I-DIC (Equations 2and 3, respectively). 12 In the fourth step, the difference image was convolved with the test image (Equation 4). In the fifth step, IM diff × IM ref and IM diff × IM test were added (Equation 5).…”

Section: Methodsmentioning

confidence: 99%

“…The objects were denoted as Obj ref and Obj test . The read function was represented by S psf, and the correlation and convolution operators were represented by * and ⊗, respectively 12.…”

mentioning

confidence: 99%

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Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation

et al. 2020

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In the treatment of human cancer, the existing drug response identification and assessment methods have some issues, such as high cost, slow processing, and low accuracy. Responsive methods that easily and indirectly assess patient tissue response to drugs or small molecules offer promising options for improving drug safety, and they are able to identify the right treatment for specific patients. Digital image correlation is a good technique that detects a part of the image between two images. In this article, a new method of correlation called significant improvement of correlation (SIC) was proposed. Data were taken from the confocal microscopy of two‐photon excited fluorescence (TPEF) probe images taken every 5 min for short‐term monitoring (STM) and long‐term monitoring (LTM; 12, 24, and 48 hours). Cells were cultured, and a new compound TPEF was tested and injected the drug. The effect of drug on the TPEF compound was assessed through correlation. Experimental and simulation results showed that the proposed SIC was better than the conventional correlation method. Results also revealed that the first three images had 0.8% correlation in STM and LTM Image15 and Image10 had 0.49% correlation. The other images demonstrated minimum correlation. Thus, the effect of the newly made drug on the cell and image had a minimum correlation.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation

et al. 2020

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“…as explained by Bing et al [19]. Results obtained through DIC is dependent on the spatial and temporal resolution of the imaging system and homogeneity of the material, as discussed by Mudassar and Butt [20]. Studies by Zhang and others [21][22][23][24][25][26] were resourceful in elaborating on the existence of a nonlinear relationship between the actual displacement of the object plane and the displacement of speckle pattern at the image plane and establishing the geometric distortion correction factor that must be applied to obtain accurate in-plane displacements.…”

Section: Introductionmentioning

confidence: 94%

GA-based laser speckle pattern digital image correlation method for surface strain measurements

Das¹,

Divo²,

Moslehy³

et al. 2020

Int. J. CMEM

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This article introduces an innovative technique that integrates a genetic algorithm (GA)-based digital image correlation with laser speckle photography for the estimation of surface displacements in structures. The images (before and after deformation) are digitized using a digital camera, and the grayscale intensity matrices are read and processed by an image processing algorithm. The two matrices of the images are then inputted into GA-based optimizer that utilizes an advanced cross-correlation fitness function to approximate the surface displacements. Furthermore, the surface strains are computed from the displacements using radial basis function differentiation and interpolation. The computed displacements are compared with simulated results obtained by the boundary element method. Close agreement between the two results proves the validity of the developed noncontact technique for accurately estimating surface displacements and strains. These experimentally estimated displacements can further be used in an inverse technique to detect and characterize subsurface cavities in structures.

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“…Numerous methods are available to quantify the response of a structural system to external loads. Existing methods, such as acoustic emission [1][2][3][4][5][6][7] and digital image correlation [8][9][10][11][12][13][14][15][16][17], offer the capability to experimentally measure/quantify/determine strains/deformations. From a modelling perspective, there are continuum-based [18][19][20] and discrete-or lattice-based [21][22][23] approaches that not only satisfy the physical laws governing the systems, but also provide abundant information required for structural analysis.…”

Section: Introductionmentioning

confidence: 99%

A Transdisciplinary Approach for Analyzing Stress Flow Patterns in Biostructures

Patel

Riveros

Thompson

et al. 2019

MCA

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This work presents a transdisciplinary, integrated approach that uses computational mechanics experiments with a flow network strategy to gain fundamental insights into the stress flow of high-performance, lightweight, structured composites by investigating the rostrum of paddlefish. Although computational mechanics experiments give an overall distribution of stress in the structural systems, stress flow patterns formed at nascent stages of loading a biostructure are hard to determine. Computational mechanics experiments on a complex model will involve a high degree of freedom thereby making the extraction of finer details computationally expensive. To address this challenge, the evolution of the stress in the rostrum is formulated as a network flow problem generated by extracting the node and connectivity information from the numerical model of the rostrum. The flow network is weighted based on the parameter of interest, which is stress in the current research. The changing kinematics of the system is provided as input to the mathematical algorithm that computes the minimum cut of the flow network. The flow network approach is verified using two simple classical problems. When applied to the model of the rostrum, the flow network approach identifies strain localization in tensile regions, and buckling/crushing in compressive regions.

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Improved Digital Image Correlation method

Cited by 24 publications

References 47 publications

Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation

Drug investigation tool: Identifying the effect of drug on cell image by using improved correlation

GA-based laser speckle pattern digital image correlation method for surface strain measurements

A Transdisciplinary Approach for Analyzing Stress Flow Patterns in Biostructures

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