Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A Digital Image Correlation Algorithm with Light Reflection Compensation


This work focuses on the influence of light reflection on Digital Images Correlation results at the macroscopic scale, and on a way to circumvent this problem. It shows that the local displacement uncertainty rises up to 5 times the usual one when a reflection occurs. An observation of the topography of the speckle reveals an important sub-pixel roughness that explains the grey level fluctuations at the pixel scale, spoiling the calculation of the gradient of the texture. To circumvent this problem, a new DIC algorithm is proposed, based on a single minimization with several pairs of images where the reflections are located in different regions. For each image, weighting functions are used to ‘exclude’ the reflection regions from the calculation, while the necessary information is obtained from the other images.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17


  1. 1.

    Grédiac M, Hild F (2012). In: Grédiac M, Hild F (eds) Full-field measurements and identification in solid mechanics. ISTE/Wiley

  2. 2.

    Sutton MA, Wolters WJ, Peters WH, Ranson WF, McNeill SR (1983) Determination of displacements using an improved digital correlation method. Image Vis Comput 1(3):133–139

  3. 3.

    Yoneyama S, Kitagawa A, Iwata S, Tani K, Kikuta H (2007) Bridge deflection measurement using digital image correlation. Exp Tech 31(1):34–40

  4. 4.

    Berring P, Knudsen HW (2006) Torsional performance of large wind turbine blades ? experimental and numerical analysis. Masters thesis, Department of Mechanical Engineering, Technical University of Denmark

  5. 5.

    Beaubier B, Dufour JE, Hild F, Roux S, Lavernhe S, Lavernhe-Taillard K (2014) CAD-Based calibration and shape measurement with stereoDIC - principle and application on test and industrial parts. Exp Mech 54(3):329–341

  6. 6.

    Grant BMB, Stone HJ, Withers PJ, Preuss M (2009) High-temperature strain field measurement using digital image correlation. J Strain Anal Eng Des 44:263–271

  7. 7.

    Kim J-H, Serpantié A, Barlat F, Pierron F, Lee M-G (2013) Characterization of the post-necking strain hardening behavior using the virtual fields method. Int J Solids Struct 50(24):3829–3842

  8. 8.

    Sedgewick J (2010) Photoshop, Scientific Imaging with, methods, measurement, and output, Chapter 6. Peachpit Press

  9. 9.

    Babaloukas G, Tentolouris N, Liatis S, Sklavounou A, Perrea D (2011) Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools. J Microsc 244(3):320–324

  10. 10.

    Gómez-Sanchis J, Moltó E, Camps-Valls G, Gómez-Chova L, Aleixos N, Blasco J (2008) Correction of the effects of the light source on spherical objects. An application to the analysis of hyperspectral images of citrus fruits. J Food Eng 85:191200

  11. 11.

    Takeda M, Mutoh K (1983) Fourier transform profilometry for the automatic measurement of 3-D object shapes. Appl Opt 22(24):3977–3982

  12. 12.

    Bornert M, Brémand F, Doumalin P, Dupré J-C, Fazzini M, Grédiac M, Hild F, Mistou S, Molimard J, Orteu JJ, Robert L, Surrel Y, Vacher P, Wattrisse B (2009) Assessment of digital image correlation measurement errors methodology and results. Mech 49:353–370

  13. 13.

    Sutton MA, Orteu J-J, Schreier H (2009) Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. Springer, New York

  14. 14.

    Besnard G, Leclerc H, Roux S, Hild F (2012) Analysis of image series through digital image correlation. J Strain Anal Eng Des 47(4):214–228

  15. 15.

    Maynadier A, Poncelet M, Lavernhe-Taillard K, Roux S (2012) One-Shot measurement of thermal and Kinematic fields: InfraRed image Correlation (IRIC). Exp Mech 52(3):241–255

  16. 16.

    Besnard G, Hild F, Lagrange J-M, Martinuzzi P, Roux S (2012) Analysis of necking in high speed experiments by stereocorrelation. Int J Impact Eng 49:179–191

  17. 17.

    Sutton MA, McNeill SR, Helm JD, Chao YJ (2000) Advances in two-dimensional and three-dimensional computer vision. In: Rastogi PK (ed) Photomechanics. Springer, Berlin Heidelberg New York, pp 323–372

  18. 18.

    Besnard G, Hild F, Roux S (2006) “Finite-element” displacement fields analysis from digital images: Application to Portevin-Le Châtelier bands. Exp Mech 46(6):789–804

  19. 19.

    Leclerc H, Perie JN, Roux S, Hild F (2009) Integrated digital image correlation for the identification of mechanical properties, MIRAGE 2009 - 4th international conference on computer vision/computer graphics collaboration techniques 5496:161–171

Download references


The authors thank the research team Eikology of the LMT-Cachan laboratory for the helpful discussion on the subject, Y. Quinsat (LURPA, ENS Cachan / CNRS EA 1385) for his help on the confocal chromatic measurement and C. Galetta and S. Mottola (Master 1 students) for their preliminary work with the authors on the reflection influence on DIC.

Author information

Correspondence to M. Poncelet.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Poncelet, M., Leclerc, H. A Digital Image Correlation Algorithm with Light Reflection Compensation. Exp Mech 55, 1317–1327 (2015).

Download citation


  • Full field measurement
  • Digital Image Correlation
  • Light reflection
  • Speckle
  • Uncertainty assessment