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Articoli di riviste sul tema "Digital image correlation"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

McCormick, Nick, and Jerry Lord. "Digital Image Correlation." Materials Today 13, no. 12 (2010): 52–54. http://dx.doi.org/10.1016/s1369-7021(10)70235-2.

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2

Wilson, Anthony J., Bianca C. Chin, Vivian M. Hsu, Michael N. Mirzabeigi, and Ivona Percec. "Digital Image Correlation." Plastic and Reconstructive Surgery 135, no. 5 (2015): 869e—876e. http://dx.doi.org/10.1097/prs.0000000000001224.

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3

Hwang, Chi Hung, Wei-Chung Wang, Yung-Hsiang Chen, and Chih-Yen Chen. "OS2-11 Multiple-Camera Semi-circular Digital Image Correlation System for Monitoring Retaining Wall(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 30. http://dx.doi.org/10.1299/jsmeatem.2015.14.30.

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4

Khaja, Abdul Aziz, and Wael A. Samad. "Hybrid Digital Image Correlation." Journal of Engineering Mechanics 146, no. 4 (2020): 04020009. http://dx.doi.org/10.1061/(asce)em.1943-7889.0001726.

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5

Xie, Huimin, and Yilan Kang. "Digital image correlation technique." Optics and Lasers in Engineering 65 (February 2015): 1–2. http://dx.doi.org/10.1016/j.optlaseng.2014.07.010.

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6

Fujimoto, Yasuhisa, Shuichi Arikawa, Riku Yoshida, Yohei Omoto, and Satoru Yoneyama. "OS2-13 Thermal Strain Measurement of Electronic Packaging Structure Using Highly Accurate Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 32. http://dx.doi.org/10.1299/jsmeatem.2015.14.32.

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7

Arikawa, Shuichi, Riku Yoshida, Satoru Yoneyama, Yasuhisa Fujimoto, and Yohei Omoto. "OS2-12 A Method for Eliminating Periodical Error for Highly Accurate Measurement in Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 31. http://dx.doi.org/10.1299/jsmeatem.2015.14.31.

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8

Kang, Huimin, zhende Hou, and Cheng Yue. "OS2-15 Measurement of Bending Response of Bone in an Electric Field Using Digital Image Correlation(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 34. http://dx.doi.org/10.1299/jsmeatem.2015.14.34.

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9

Karino, Keiji, and Takuma Matsuo. "OS2-9 Non-contact Deflection Measurement for Health Monitoring of Overpass by Using Digital Image Correlation Method(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 28. http://dx.doi.org/10.1299/jsmeatem.2015.14.28.

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10

Yang, J., and K. Bhattacharya. "Combining Image Compression with Digital Image Correlation." Experimental Mechanics 59, no. 5 (2019): 629–42. http://dx.doi.org/10.1007/s11340-018-00459-y.

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11

Neggers, J., B. Blaysat, J. P. M. Hoefnagels, and M. G. D. Geers. "On image gradients in digital image correlation." International Journal for Numerical Methods in Engineering 105, no. 4 (2015): 243–60. http://dx.doi.org/10.1002/nme.4971.

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12

Sjödahl, Mikael. "Gradient Correlation Functions in Digital Image Correlation." Applied Sciences 9, no. 10 (2019): 2127. http://dx.doi.org/10.3390/app9102127.

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Abstract (sommario):

The performance of seven different correlation functions applied in Digital Image Correlation has been investigated using simulated and experimentally acquired laser speckle patterns. The correlation functions were constructed as combinations of the pure intensity correlation function, the gradient correlation function and the Hessian correlation function, respectively. It was found that the correlation function that was constructed as the product of all three pure correlation functions performed best for the small speckle sizes and large correlation values, respectively. The difference betwee

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13

Tomičevć, Zvonimir, François Hild, and Stéphane Roux. "Mechanics-aided digital image correlation." Journal of Strain Analysis for Engineering Design 48, no. 5 (2013): 330–43. http://dx.doi.org/10.1177/0309324713482457.

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14

Shen, Huan, Peize Zhang, and Xiang Shen. "Kernel based Digital Image Correlation." International Journal of Signal Processing, Image Processing and Pattern Recognition 8, no. 3 (2015): 261–72. http://dx.doi.org/10.14257/ijsip.2015.8.3.24.

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15

Yang, J., and K. Bhattacharya. "Augmented Lagrangian Digital Image Correlation." Experimental Mechanics 59, no. 2 (2018): 187–205. http://dx.doi.org/10.1007/s11340-018-00457-0.

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16

Mudassar, Asloob Ahmad, and Saira Butt. "Improved Digital Image Correlation method." Optics and Lasers in Engineering 87 (December 2016): 156–67. http://dx.doi.org/10.1016/j.optlaseng.2015.10.002.

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17

Curt, J., M. Capaldo, F. Hild, and S. Roux. "Optimal digital color image correlation." Optics and Lasers in Engineering 127 (April 2020): 105896. http://dx.doi.org/10.1016/j.optlaseng.2019.105896.

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18

Sakaue, Kenich, Susumu Ohki, and Shinichi Suzuki. "OS2-6 Discussion on Energy Allocation problem into Branch Cracks by using Stationary Bifurcated Crack and Digital Image Correlation(Digital image correlation and its applications (2),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 25. http://dx.doi.org/10.1299/jsmeatem.2015.14.25.

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19

Chen, Terry Yuan-Fang, and Ren-Shiang Lu. "OS2-2 Development of a Hybrid Infrared Image Correlation Technique to deformation measurement of Composites(Digital image correlation and its applications (1),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 21. http://dx.doi.org/10.1299/jsmeatem.2015.14.21.

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20

Pan, Bing, and Long Tian. "OS2-8 Real-time, Non-contact and Targetless Measurement of Vertical Deflection of Bridges using Off-axis Digital Image Correlation(Digital image correlation and its applications (3),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 27. http://dx.doi.org/10.1299/jsmeatem.2015.14.27.

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21

Shin, Bumshick, and KyuHan Kim. "Analysis of Wave-Induced Current Using Digital Image Correlation Techniques." Journal of Sensors 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/1784507.

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Abstract (sommario):

Recently, advancement of digital image techniques and communications technology has enabled the application of existing images for scientific purposes. Furthermore, both quantitative and qualitative analyses of images have become possible through image processing such as transmit/storage of digital image data and image rectification. In this study, a coast having representative characteristics of east coast of Korea was selected with having erosion in winter, and the sedimentation in summer takes place repeatedly. Three-dimensional hydraulic model test was conducted to analyze its outcomes by

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22

Chen, Wei, Zhenyu Jiang, and Liqun Tang. "OS2-3 A Comparison of Accuracy and Convergence Capability between IC-GN Algorithm and FA-NR Algorithm in Digital Image Correlation(Digital image correlation and its applications (1),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 22. http://dx.doi.org/10.1299/jsmeatem.2015.14.22.

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23

Chen, Lin, Rong Sheng Lu, Yan Qiong Shi, and Jian Sheng Tian. "A Differential Evolution Stereo Matching Method in Digital Image Correlation." Key Engineering Materials 625 (August 2014): 297–304. http://dx.doi.org/10.4028/www.scientific.net/kem.625.297.

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Stereo matching is widely used in three-dimensional (3D) reconstruction, stereo machine vision and digital image correlation. The aim of stereo matching process is to solve the well-known correspondence problem, which tries to match points or features from one image with the same points or features in another image from the same 3D scene. There are two basic ways, correlation-based and feature-based, are used to find the correspondences between two images. The correlation-based way is to determine if one location in one image looks/seems like another in another image, and the feature-based way

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24

Lin, Zhe, Tian Cai, and Yanfeng Wang. "Parallel reliability-guided algorithm for digital image correlation." Insight - Non-Destructive Testing and Condition Monitoring 61, no. 12 (2019): 729–37. http://dx.doi.org/10.1784/insi.2019.61.12.729.

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Abstract (sommario):

Digital image correlation is a non-contact optical method for measuring the displacement and strain on the surface of a material. The existing reliability-guided digital image correlation (RG-DIC) method is stable and reliable for a single image but it still needs a large calculational resource for a sequence of images. Due to the decorrelation effect, the reference image must be replaced several times to correct the measurement results for an image sequence involving a large deformation or a discontinuous deformation. Since the process must be executed sequentially, image by image, the total

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25

Forsey, A., and S. Gungor. "Demosaicing images from colour cameras for digital image correlation." Optics and Lasers in Engineering 86 (November 2016): 20–28. http://dx.doi.org/10.1016/j.optlaseng.2016.05.006.

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26

Chen, Jiangping, and Weijun Tao. "Gradient-Based Automatic Exposure Control for Digital Image Correlation." Sustainability 15, no. 2 (2023): 1149. http://dx.doi.org/10.3390/su15021149.

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Abstract (sommario):

Digital image correlation (DIC) is widely used in material experiments such as ores; the quality of a speckle image directly affects the accuracy of the DIC calculation. This study aims to acquire high-quality speckle pattern images and improve the calculation accuracy and stability. A gradient-based image quality metric was selected to evaluate the image quality, and its validity was verified by a rigid body experiment and a numerical experiment. Based on the maximum image quality metric, an automatic exposure control algorithm and the control procedure were proposed to obtain the optimal exp

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27

López-Ávila, Luis Felipe, and Josué Álvarez-Borrego. "Fractional Fourier Transform for Digital Image Recognition." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 10 (2020): 2054025. http://dx.doi.org/10.1142/s0218001420540257.

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Abstract (sommario):

In the image recognition field, there are several techniques that allow identifying patterns in digital images, correlation being one of them. In a correlation, you have to obtain an output plane that is as clean as possible. To measure the sharpness of the correlation peak and the cleanliness of the output plane, a performance metric called Peak to Correlation Energy (PCE) is used. In this paper, the fractional correlation is applied to recognize real phytoplankton images. This fractional correlation guarantees a higher PCE compared to the conventional correlation. The results of PCE are two-

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28

Kojima, Yuka, Hiroshi Hohjo, Takashi Ohta, and Hiroaki Makino. "OS2-14 Visualization of Non-uniform Microscopic Distribution of Thermal Strains in Glass-fiber-cloth/epoxy Laminates by Digital Image Correlation Method(Digital image correlation and its applications (4),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 33. http://dx.doi.org/10.1299/jsmeatem.2015.14.33.

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29

Barros, Francisco, Pedro J. Sousa, Paulo J. Tavares, and Pedro MGP Moreira. "Digital image correlation through image registration in the frequency domain." Journal of Strain Analysis for Engineering Design 53, no. 8 (2018): 575–83. http://dx.doi.org/10.1177/0309324718802705.

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Abstract (sommario):

The present work analyses displacement field computations for several digital image correlation test cases obtained through the application of image registration in the Fourier domain. The applied method relies on the properties of the discrete Fourier transform with regard to the cross-correlation function to find the rigid displacement between two subsets. The computed displacement fields were compared to their analogous values obtained through a commercial digital image correlation code. The test cases cover both two-dimensional and three-dimensional digital image correlation and make use o

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30

Atkinson, Devan, and Thorsten Hermann Becker. "Stereo Digital Image Correlation in MATLAB." Applied Sciences 11, no. 11 (2021): 4904. http://dx.doi.org/10.3390/app11114904.

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Digital Image Correlation (DIC) has found widespread use in measuring full-field displacements and deformations experienced by a body from images captured of it. Stereo-DIC has received significantly more attention than two-dimensional (2D) DIC since it can account for out-of-plane displacements. Although many aspects of Stereo-DIC that are shared in common with 2D DIC are well documented, there is a lack of resources that cover the theory of Stereo-DIC. Furthermore, publications which do detail aspects of the theory do not detail its implementation in practice. This literature gap makes it di

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31

McCormick, Nick, and Jerry Lord. "Digital image correlation for structural measurements." Proceedings of the Institution of Civil Engineers - Civil Engineering 165, no. 4 (2012): 185–90. http://dx.doi.org/10.1680/cien.11.00040.

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32

Murray, Chris A., Neil A. Hoult, and W. Andy Take. "Dynamic measurements using digital image correlation." International Journal of Physical Modelling in Geotechnics 17, no. 1 (2017): 41–52. http://dx.doi.org/10.1680/jphmg.15.00055.

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33

Cofaru, Corneliu, Wilfried Philips, and Wim Van Paepegem. "Pixel-level robust digital image correlation." Optics Express 21, no. 24 (2013): 29979. http://dx.doi.org/10.1364/oe.21.029979.

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34

Withers, Philip J. "Strain Measurement by Digital Image Correlation." Strain 44, no. 6 (2008): 421–22. http://dx.doi.org/10.1111/j.1475-1305.2008.00556.x.

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35

Baldi, A. "Digital Image Correlation and Color Cameras." Experimental Mechanics 58, no. 2 (2017): 315–33. http://dx.doi.org/10.1007/s11340-017-0347-2.

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36

SU, Yong, QingChuan ZHANG, and XiaoPing WU. "Progress in digital image correlation method." SCIENTIA SINICA Physica, Mechanica & Astronomica 48, no. 9 (2018): 094604. http://dx.doi.org/10.1360/sspma2018-00156.

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37

Wang, Min, Hao Wang, and Yuwan Cen. "High-speed digital-image correlation method." Optics Letters 34, no. 13 (2009): 1955. http://dx.doi.org/10.1364/ol.34.001955.

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38

Dupré, J. C., M. Bornert, L. Robert, and B. Wattrisse. "Digital image correlation: displacement accuracy estimation." EPJ Web of Conferences 6 (2010): 31006. http://dx.doi.org/10.1051/epjconf/20100631006.

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39

Tavares, Paulo J., Tiago Ramos, Daniel Braga, Mario A. P. Vaz, and Pedro Miguel Guimarães Pires Moreira. "SIF determination with digital image correlation." International Journal of Structural Integrity 6, no. 6 (2015): 668–76. http://dx.doi.org/10.1108/ijsi-03-2015-0010.

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Abstract (sommario):

Purpose – Hybrid methods, wherefore numerical and experimental data are used to calculate a critical parameter, have been used for several years with great success in Experimental Mechanics and, in particular, in fracture mechanics. The purpose of this paper is to report on the comparison of the strain field from numerical modelling forecasts against the experimental data obtained with the digital image correlation method under Mode II loading in fatigue testing. The numerical dual boundary element method has been established in the past as a very reliable method near singular regions where st

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40

Pan, B. "Recent Progress in Digital Image Correlation." Experimental Mechanics 51, no. 7 (2010): 1223–35. http://dx.doi.org/10.1007/s11340-010-9418-3.

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41

Jones, E. M. C., E. C. Quintana, P. L. Reu, and J. L. Wagner. "X-Ray Stereo Digital Image Correlation." Experimental Techniques 44, no. 2 (2019): 159–74. http://dx.doi.org/10.1007/s40799-019-00339-7.

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42

Neggers, J., J. P. M. Hoefnagels, M. G. D. Geers, F. Hild, and S. Roux. "Time-resolved integrated digital image correlation." International Journal for Numerical Methods in Engineering 103, no. 3 (2015): 157–82. http://dx.doi.org/10.1002/nme.4882.

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43

Jia, Zhaoyang, and Guangxue Chen. "Study on Digital Image Inpainting Method Based on Multispectral Image Decomposition Synthesis." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 01 (2018): 1954004. http://dx.doi.org/10.1142/s0218001419540041.

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The paper analyzes the image inpainting problem of damaged Painting Arts for high fidelity images reproduction, and a digital image inpainting method based on multispectral image decomposition synthesis is proposed. Firstly, multi-channel images of Painting Arts are obtained by multispectral technology. Then, a polynomial regression method based on principal component is used to reconstruct the spectral image. The reconstructed image is decomposed by VO image decomposition model. During the inpainting process, the channel correlation of the structure image and the texture image of multispectra

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44

Vaitkunas, Tomas, Paulius Griskevicius, and Adi Adumitroaie. "Peridynamic Approach to Digital Image Correlation Strain Calculation Algorithm." Applied Sciences 12, no. 13 (2022): 6550. http://dx.doi.org/10.3390/app12136550.

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Abstract (sommario):

Digital image correlation is an experimental optical non-contact full field displacement and strain evaluation method based on the surface subsets tracking with photo cameras, digital images processing, and numerical computation. However, the full field of strain computation is a challenging problem, mainly because the displacement field to be differentiated is not continuous, individual subsets are tracked by the optical digital image correlation system. Moreover, the numerical differentiation can also amplify the noise of the displacement field inducing thus strain errors when the displaceme

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45

Oh, Ju Hwan, Jong Min Kim, and Cheol Soo Lee. "Digital Image Correlation using Image Calibration under Restricted Environment." Journal of the Korean Society of Manufacturing Technology Engineers 30, no. 4 (2021): 323–31. http://dx.doi.org/10.7735/ksmte.2021.30.4.323.

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46

Besnard, Gilles, Hugo Leclerc, François Hild, Stéphane Roux, and Nicolas Swiergiel. "Analysis of image series through global digital image correlation." Journal of Strain Analysis for Engineering Design 47, no. 4 (2012): 214–28. http://dx.doi.org/10.1177/0309324712441435.

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47

Pan, Bing. "Reliability-guided digital image correlation for image deformation measurement." Applied Optics 48, no. 8 (2009): 1535. http://dx.doi.org/10.1364/ao.48.001535.

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48

Crammond, G., S. W. Boyd, and Janice M. Dulieu-Barton. "Speckle Pattern Characterisation for High Resolution Digital Image Correlation." Applied Mechanics and Materials 70 (August 2011): 261–66. http://dx.doi.org/10.4028/www.scientific.net/amm.70.261.

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Abstract (sommario):

Digital image correlation (DIC) is an optical technique for full field deformation measurement. The spatial resolution and precision of the measurements are limited by the number of pixels within the image. The use of magnifying optics provides greater spatial resolution images, enabling smaller displacements to be observed with greater accuracy. Increasing the magnification of an image significantly changes the appearance of the non-periodic, stochastic speckle pattern which provides the grey scale contrast necessary for the image correlation method. In the paper a methodology is developed to

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49

Koyama, Hiroto, and Eisaku Umezaki. "OS2-7 Behavior of Ultraviolet-Curable Resin during Curing(Digital image correlation and its applications (2),OS2 Digital image correlation and its applications,MEASUREMENT METHODS)." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2015.14 (2015): 26. http://dx.doi.org/10.1299/jsmeatem.2015.14.26.

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50

Berveglieri, Adilson, and Antonio Tommaselli. "Reconstruction of Cylindrical Surfaces Using Digital Image Correlation." Sensors 18, no. 12 (2018): 4183. http://dx.doi.org/10.3390/s18124183.

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Abstract (sommario):

A technique for the reconstruction of cylindrical surfaces using optical images with an extension of least squares matching is presented. This technique is based on stereo-image acquisition of a cylindrical object, and it involves displacing the camera following the object length. The basic concept behind this technique is that variations in the camera viewpoint over a cylindrical object produce perspective effects similar to a conic section in an image sequence. Such parallax changes are continuous and can be modelled by a second-order function, which is combined with an adaptive least square

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