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Digital volume correlation in an environment with intensive salt-and-pepper noise and strong monotonic nonlinear distortion of light intensity

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Języki publikacji
EN
Abstrakty
EN
Digital volume correlation is an image-based technique for internal 3D displacement and strain fields measurement or analysis widely used in the field of experimental mechanics. A widely used correlation function (criterion) of digital volume correlation is Pearson correlation function, which suffers from the problem of the acquired data being contaminated by salt-and-pepper noise and monotonic nonlinear distortion of the light intensity. In this work, a 3D correlation function called the Spearman correlation function is used to deal with those interferences. A numerical experiment shows that the performance of Spearman correlation function using integer-pixel registration in an environment with 10% salt-and-pepper noise is better than that of Spearman and Pearson correlation functions using sub-pixel registration in an environment with 1% salt-and-pepper noise. As the light intensity distortion is significant, the error of Pearson correlation function is considerable; meanwhile, the error of Spearman correlation function is small. In conclusion, Spearman correlation function is, in particular, practical and useful in digital volume correlation.
Czasopismo
Rocznik
Strony
209--223
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
autor
  • School of Printing and Packaging, Wuhan University, Wuhan, P.R. China, 430072
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
autor
  • School of Automation, Guangdong University of Technology, Guangzhou, P.R. China, 510006
Bibliografia
  • [1] LECLERC H., PÉRIÉ J.-N., ROUX S., HILD F., Voxel-scale digital volume correlation, Experimental Mechanics 51(4), 2011, pp. 479–490.
  • [2] FEDELE R., CIANI A., FIORI F., X -ray microtomography under loading and 3D-volume digital image correlation. A review, Fundamenta Informaticae 135(1–2), 2014, pp. 171–197.
  • [3] BING PAN, DAFANG WU, ZHAOYANG WANG, Internal displacement and strain measurement using digital volume correlation: a least-squares framework, Measurement Science and Technology 23(4), 2012, article ID 045002.
  • [4] BAY B.K., SMITH T.S., FYHRIE D.P., SAAD M., Digital volume correlation: three-dimensional strain mapping using X-ray tomography, Experimental Mechanics 39(3), 1999, pp. 217–226.
  • [5] BAY B.K., Methods and applications of digital volume correlation, Journal of Strain Analysis for Engineering Design 43(8), 2008, pp. 745–760.
  • [6] SMITH T.S., BAY B.K., RASHID M.M., Digital volume correlation including rotational degrees of freedom during minimization, Experimental Mechanics 42(3), 2002, pp. 272–278.
  • [7] GATES M., LAMBROS J., HEATH M.T., Towards high performance digital volume correlation, Experimental Mechanics 51(4), 2011, pp. 491–507.
  • [8] BING PAN, BO WANG, DAFANG WU, LUBINEAU G., An efficient and accurate 3D displacements tracking strategy for digital volume correlation, Optics and Lasers in Engineering 58, 2014, pp. 126–135.
  • [9] WANG T., JIANG Z., KEMAO Q., LIN F., SOON S.H., GPU accelerated digital volume correlation, Experimental Mechanics 56(2), 2016, pp. 297–309.
  • [10] GATES M., HEATH M.T., LAMBROS J., High-performance hybrid CPU and GPU parallel algorithm for digital volume correlation, International Journal of High Performance Computing Applications 29(1), 2015, pp. 92–106.
  • [11] BAR-KOCHBA E., TOYJANOVA J., ANDREWS E., KIM K.-S., FRANCK C., A fast iterative digital volume correlation algorithm for large deformations, Experimental Mechanics 55(1), 2015, pp. 261–274.
  • [12] LI LIU, MORGAN E.F., Accuracy and precision of digital volume correlation in quantifying displacements and strains in trabecular bone, Journal of Biomechanics 40(15), 2007, pp. 3516–3520.
  • [13] ZAUEL R., YENI Y.N., BAY B.K., DONG X.N., FYHRIE D.P., Comparison of the linear finite element prediction of deformation and strain of human cancellous bone to 3D digital volume correlation measurements, Journal of Biomechanical Engineering 128(1), 2006, pp. 1–6.
  • [14] LENOIR N., BORNERT M., DESRUES J., BÉSUELLE P., VIGGIANI G., Volumetric digital image correlation applied to X-ray microtomography images from triaxial compression tests on argillaceous rock, Strain 43(3), 2007, pp. 193–205.
  • [15] FORSBERG F., SJÖDAHL M., MOOSER R., HACK E., WYSS P., Full three-dimensional strain measurements on wood exposed to three-point bending: analysis by use of digital volume correlation applied to synchrotron radiation microcomputed tomography image data, Strain 46(1), 2010, pp. 47–60.
  • [16] FORSBERG F., SIVIOUR C.R., 3D deformation and strain analysis in compacted sugar using X-ray microtomography and digital volume correlation, Measurement Science and Technology 20(9), 2009, article ID 095703.
  • [17] HALL S.A., BORNERT M., DESRUES J., PANNIER Y., LENOIR N., VIGGIANI G., BÉSUELLE P., Discrete and continuum analysis of localised deformation in sand using X-ray μCT and volumetric digital image correlation, Géotechnique 60(5), 2010, pp. 315–322.
  • [18] RANNOU J., LIMODIN N., RÉTHORÉ J., GRAVOUIL A., LUDWIG W., BAÏETTO-DUBOURG M.-C., BUFFIÈRE J.-Y., COMBESCURE A., HILD F., ROUX S., Three dimensional experimental and numerical multiscale analysis of a fatigue crack, Computer Methods in Applied Mechanics and Engineering 199(21–22), 2010, pp. 1307–1325.
  • [19] CARROLL J., EFSTATHIOU C., LAMBROS J., SEHITOGLU H., HAUBER B., SPOTTSWOOD S., CHONA R., Investigation of fatigue crack closure using multiscale image correlation experiments, Engineering Fracture Mechanics 76(15), 2009, pp. 2384–2398.
  • [20] FISHER R.A., On the ‘probable error’ of a coefficient of correlation deduced from a small sample, Metron 1, 1921, pp. 3–32.
  • [21] KENDALL M., GIBBONS J.D., Rank Correlation Methods, 5th Edition, Oxford University Press, New York, 1990.
  • [22] MARI D.D., KOTZ S., Correlation and Dependence, Imperial College Press, London, 2001.
  • [23] WEICHAO XU, CHUNQI CHANG, HUNG Y.S., KWAN S.K., PETER CHIN WAN FUNG, Order statistics correlation coefficient as a novel association measurement with applications to biosignal analysis, IEEE Transactions on Signal Processing 55(12), 2007, pp. 5552–5563.
  • [24] WEICHAO XU, CHUNQI CHANG, HUNG Y.S., PETER CHIN WAN FUNG, Asymptotic properties of order statistics correlation coefficient in the normal cases, IEEE Transactions on Signal Processing 56(6), 2008, pp. 2239–2248.
  • [25] WEICHAO XU, YUNHE HOU, HUNG Y.S., YUEXIAN ZOU, A comparative analysis of Spearman’s rho and Kendall’s tau in normal and contaminated normal models, Signal Processing 93(1), 2013, pp. 261–276.
  • [26] PAN BING, XIE HUI-MIN, XU BO-QIN, DAI FU-LONG, Performance of sub-pixel registration algorithms in digital image correlation, Measurement Science and Technology 17(6), 2006, pp. 1615–1621.
  • [27] BING PAN, HUIMIN XIE, ZHAOYANG WANG, Equivalence of digital image correlation criteria for pattern matching, Applied Optics 49(28), 2010, pp. 5501–5509.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d7633769-ec62-4aad-9018-64e569eace5c
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