OSA's Digital Library

Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 19 — Jul. 1, 2013
  • pp: 4681–4692

Deformation measurements by digital image correlation with automatic merging of data distributed in time

Marcin Malesa and Malgorzata Kujawinska  »View Author Affiliations

Applied Optics, Vol. 52, Issue 19, pp. 4681-4692 (2013)

View Full Text Article

Enhanced HTML    Acrobat PDF (1447 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



This paper presents a method to analyze 3D displacement data captured by digital image correlation (DIC) method over a long period of time. It allows monitoring of an object when a 3D DIC setup is not fixed in the same position between a consecutive series of measurements. An implementation of the data merging procedure is described and a proof of concept is provided using example measurements for both a numerical model and a real experiment in laboratory conditions. We evaluated the accuracy and discuss the main sources of errors. The obtained results prove the method is feasible for in situ long-term measurements and monitoring in industry and civil engineering.

© 2013 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(150.3045) Machine vision : Industrial optical metrology
(150.5495) Machine vision : Process monitoring and control

ToC Category:
Machine Vision

Original Manuscript: March 15, 2013
Revised Manuscript: May 24, 2013
Manuscript Accepted: May 26, 2013
Published: June 27, 2013

Marcin Malesa and Malgorzata Kujawinska, "Deformation measurements by digital image correlation with automatic merging of data distributed in time," Appl. Opt. 52, 4681-4692 (2013)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. T. Chu, W. Ranson, M. Sutton, and W. Peters, “Applications of digital image correlation techniques to experimental mechanics,” Exp. Mech. 25, 232–244 (1985). [CrossRef]
  2. M. Sutton, J. J. Orteu, and H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements (Springer, 2009).
  3. B. Pan, “Recent progress in digital image correlation,” Exp. Mech. 51, 1223–1235 (2011). [CrossRef]
  4. J. J. Orteu, “3D computer vision in experimental mechanics,” Opt. Lasers Eng. 47, 282–291 (2009). [CrossRef]
  5. A. Piekarczuk, M. Malesa, M. Kujawinska, and K. Malowany, “Application of hybrid fem-dic method for assessment of low-cost building structures,” Exp. Mech. 52, 1297–1311 (2012). [CrossRef]
  6. Y.-q. Tan, L. Zhang, M. Guo, and L.-y. Shan, “Investigation of the deformation properties of asphalt mixtures with DIC technique,” Constr. Build. Mater. 37, 581–590 (2012). [CrossRef]
  7. S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007). [CrossRef]
  8. J. Travelletti, C. Delacourt, P. Allemand, J.-P. Malet, R. Schmittbuhl, R. Toussaint, and M. Bastard, “Correlation of multi-temporal ground-based optical images for landslide monitoring: application, potential, and limitations,” ISPRS J. Photogramm. Remote Sens. 70, 39–55 (2012). [CrossRef]
  9. M. Kujawinska, M. Malesa, K. Malowany, and P. M. Blaszczyk, “Application of image-based methods for monitoring and measurements of structures in power stations,” Key Eng. Mater. 518, 24–36 (2012). [CrossRef]
  10. M. Malesa, K. Malowany, L. Tyminska-Widmer, E. A. Kwiatkowska, M. Kujawinska, B. J. Rouba, and P. Targowski, “Application of digital image correlation (DIC) for tracking deformations of paintings on canvas,” Proc. SPIE 8084, 80840L (2011). [CrossRef]
  11. D. Khennouf, J. Dulieu-Barton, A. R. Chambers, F. J. Lennard, and D. Eastop, “Assessing the feasibility of monitoring strain in historical tapestries using digital image correlation,” Strain 46, 19–32 (2010). [CrossRef]
  12. B. Pan, D. Wu, and L. Yu, “Optimization of a three-dimensional digital image correlation system for deformation measurements in extreme environments,” Appl. Opt. 51, 4409–4419 (2012). [CrossRef]
  13. T. N. Nguyen, J. M. Huntley, R. L. Burguete, and C. R. Coggrave, “Shape and displacement measurement of discontinuous surfaces by combining fringe projection and digital image correlation,” Opt. Eng. 50, 101505 (2011). [CrossRef]
  14. B. Pan, D. Wu, and Y. Xia, “An active imaging digital image correlation method for deformation measurement insensitive to ambient light,” Opt. Laser Technol. 44, 204–209 (2012). [CrossRef]
  15. Q. Ma and S. Ma, “Experimental investigation of the systematic error on photomechanic methods induced by camera self-heating,” Opt. Express 21, 7686–7698 (2013). [CrossRef]
  16. J. Sładek, K. Ostrowska, P. Kohut, K. Holak, A. Gaska, and T. Uhl, “Development of a vision-based deflection measurement system and its accuracy assessment,” Measurement 46, 1237–1249 (2013). [CrossRef]
  17. M. Malesa and M. Kujawinska, “Modified two-dimensional digital image correlation method with capability of merging of data distributed in time,” Appl. Opt. 51, 8641–8655 (2012). [CrossRef]
  18. G. Bradski and A. Kaehler, Learning Open CV: Computer Vision with the Open CV Library, (O’Reilly, 2008).
  19. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge, 2004).
  20. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).
  21. R. Keys, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992). [CrossRef]
  22. The Blender Foundation, “Blender user manual,” 2013, http://wiki.blender.org/index.php/Doc:2.6/Manual .
  23. H. W. Schreier, J. R. Braasch, and M. A. Sutton, “Systematic errors in digital image correlation caused by intensity interpolation,” Opt. Eng. 39, 2915–2921 (2000). [CrossRef]
  24. R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29, 1153–1160 (1981). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited