Skip to main content

Abstract

A predictive formula giving the measurement resolution in displacement maps obtained using Digital Image Correlation was proposed some years ago in the literature. The objective of this paper is to revisit this formula and to propose a more general one which takes into account the influence of subpixel interpolation for the displacement. Moreover, a noiseless DIC tangent operator is defined to also minimizes noise propagation from images to displacement maps. Simulated data enable us to assess the improvement brought about by this approach. The experimental validation is then carried out by assessing the noise in displacement maps deduced from a stack of images corrupted by noise. It is shown that specific image pre-processing tools are required to correctly predict the displacement resolution. This image pre-processing step is necessary to correctly account for the fact that noise in images is signal-dependent, and to get rid of parasitic micro-movements between camera and specimen that were experimentally observed and which corrupt noise estimation. Obtained results are analyzed and discussed.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. JCGM. International Vocabulary of Metrology—Basic and General Concepts and Associated Terms (VIM), vol. 200 (BIPM, 2012)

    Google Scholar 

  2. A. Chrysochoos, Y. Surrel, Basics of metrology and introduction to techniques, Chapter one, in Full-field measurements and identification in solid mechanics, ed. by M. Grédiac, F. Hild (Wiley, New York, 2012), pp. 1–29

    Chapter  Google Scholar 

  3. Z.Y. Wang, H.Q. Li, J.W. Tong, J.T. Ruan, Statistical analysis of the effect of intensity pattern noise on the displacement measurement precision of digital image correlation using self-correlated images. Exp. Mech. 47(5), 701–707 (2007)

    Article  Google Scholar 

  4. G. Besnard, F. Hild, S. Roux, Finite-element displacement fields analysis from digital images: application to Portevin-Le Châtelier bands. Exp. Mech. 46(6), 789–803 (2006)

    Article  Google Scholar 

  5. J. Réthoré, G. Besnard, G. Vivier, F. Hild, S. Roux, Experimental investigation of localized phenomena using digital image correlation. Philos. Mag. 88(28–29), 3339–3355 (2008)

    Article  Google Scholar 

  6. B. Blaysat, M. Grédiac, F. Sur, The effect of interpolation in noise propagation from images to DIC displacement maps (2015, submitted)

    Google Scholar 

  7. M. Grédiac, F. Sur, Effect of sensor noise on the resolution and spatial resolution of the displacement and strain maps obtained with the grid method. Strain 50(1), 1–27 (2014)

    Article  Google Scholar 

  8. A. Foi, M. Trimeche, V. Katkovnik, K. Egiazarian, Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data. IEEE Trans. Image Process. 17(10), 1737–1754 (2008)

    Article  MathSciNet  Google Scholar 

  9. G.E. Healey, R. Kondepudy, Radiometric CCD camera calibration and noise estimation. IEEE Trans. Pattern Anal. Mach. Intell. 16(3), 267–276 (1994)

    Article  Google Scholar 

  10. F. Sur, M. Grédiac, Sensor noise modeling by stacking pseudo-periodic grid images affected by vibrations. IEEE Signal Process. Lett. 21(4), 432–436 (2014)

    Article  Google Scholar 

  11. R. Fedele, L. Galantucci, A. Ciani, Global 2D digital image correlation for motion estimation in a finite element framework: a variational formulation and a regularized, pyramidal, multi-grid implemen-tation. Int. J. Numer. Methods Eng. 96(12), 739–762 (2013)

    Article  Google Scholar 

  12. B. Blaysat, M. Grédiac, F. Sur, On the propagation of camera sensor noise to displacement maps obtained by DIC—an experimental study (2015, submitted)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 The Society for Experimental Mechanics, Inc.

About this paper

Cite this paper

Blaysat, B., Grédiac, M., Sur, F. (2016). On Noise Prediction in Maps Obtained With Global DIC. In: Jin, H., Yoshida, S., Lamberti, L., Lin, MT. (eds) Advancement of Optical Methods in Experimental Mechanics, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-22446-6_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-22446-6_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22445-9

  • Online ISBN: 978-3-319-22446-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics