Abstract

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

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  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]

2013 (2)

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]

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]

2012 (7)

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]

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]

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]

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]

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]

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]

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]

2011 (3)

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]

B. Pan, “Recent progress in digital image correlation,” Exp. Mech. 51, 1223–1235 (2011).
[CrossRef]

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]

2010 (1)

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]

2009 (1)

J. J. Orteu, “3D computer vision in experimental mechanics,” Opt. Lasers Eng. 47, 282–291 (2009).
[CrossRef]

2007 (1)

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

2000 (1)

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]

1992 (1)

R. Keys, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992).
[CrossRef]

1985 (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]

1981 (1)

R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29, 1153–1160 (1981).
[CrossRef]

Allemand, P.

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]

Bastard, M.

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]

Blaszczyk, P. M.

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]

Braasch, J. R.

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]

Bradski, G.

G. Bradski and A. Kaehler, Learning Open CV: Computer Vision with the Open CV Library, (O’Reilly, 2008).

Burguete, R. L.

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]

Chambers, A. R.

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]

Chu, T.

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]

Coggrave, C. R.

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]

Delacourt, C.

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]

Dulieu-Barton, J.

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]

Eastop, D.

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]

Flannery, B. P.

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).

Gaska, A.

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]

Guo, M.

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]

Hartley, R.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge, 2004).

Holak, K.

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]

Huntley, J. M.

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]

Iwata, S.

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Kaehler, A.

G. Bradski and A. Kaehler, Learning Open CV: Computer Vision with the Open CV Library, (O’Reilly, 2008).

Keys, R.

R. Keys, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992).
[CrossRef]

R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29, 1153–1160 (1981).
[CrossRef]

Khennouf, D.

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]

Kihuta, H.

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Kitagawa, A.

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Kohut, P.

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]

Kujawinska, M.

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]

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]

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]

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]

Kwiatkowska, E. A.

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]

Lennard, F. J.

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]

Ma, Q.

Ma, S.

Malesa, M.

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]

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]

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]

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]

Malet, J.-P.

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]

Malowany, K.

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]

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]

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]

Nguyen, T. N.

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]

Orteu, J. J.

J. J. Orteu, “3D computer vision in experimental mechanics,” Opt. Lasers Eng. 47, 282–291 (2009).
[CrossRef]

M. Sutton, J. J. Orteu, and H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements (Springer, 2009).

Ostrowska, K.

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]

Pan, B.

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]

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]

B. Pan, “Recent progress in digital image correlation,” Exp. Mech. 51, 1223–1235 (2011).
[CrossRef]

Peters, W.

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]

Piekarczuk, A.

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]

Press, W. H.

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).

Ranson, W.

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]

Rouba, B. J.

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]

Schmittbuhl, R.

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]

Schreier, H.

M. Sutton, J. J. Orteu, and H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements (Springer, 2009).

Schreier, H. W.

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]

Shan, L.-y.

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]

Sladek, J.

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]

Sutton, M.

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]

M. Sutton, J. J. Orteu, and H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements (Springer, 2009).

Sutton, M. A.

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]

Tan, Y.-q.

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]

Tani, K.

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Targowski, P.

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]

Teukolsky, S. A.

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).

Toussaint, R.

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]

Travelletti, J.

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]

Tyminska-Widmer, L.

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]

Uhl, T.

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]

Vetterling, W. T.

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).

Wu, D.

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]

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]

Xia, Y.

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]

Yoneyama, S.

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Yu, L.

Zhang, L.

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]

Zisserman, A.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge, 2004).

Appl. Opt. (2)

Constr. Build. Mater. (1)

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]

Exp Tech. (1)

S. Yoneyama, A. Kitagawa, S. Iwata, K. Tani, and H. Kihuta, “Bridge deflection measurement using digital image correlation,” Exp Tech. 3134–40 (2007).
[CrossRef]

Exp. Mech. (3)

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]

B. Pan, “Recent progress in digital image correlation,” Exp. Mech. 51, 1223–1235 (2011).
[CrossRef]

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]

IEEE Trans. Acoust. Speech Signal Process. (1)

R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29, 1153–1160 (1981).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

R. Keys, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992).
[CrossRef]

ISPRS J. Photogramm. Remote Sens. (1)

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]

Key Eng. Mater. (1)

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]

Measurement (1)

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]

Opt. Eng. (2)

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]

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]

Opt. Express (1)

Opt. Laser Technol. (1)

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]

Opt. Lasers Eng. (1)

J. J. Orteu, “3D computer vision in experimental mechanics,” Opt. Lasers Eng. 47, 282–291 (2009).
[CrossRef]

Proc. SPIE (1)

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]

Strain (1)

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]

Other (5)

M. Sutton, J. J. Orteu, and H. Schreier, Image Correlation for Shape, Motion and Deformation Measurements (Springer, 2009).

G. Bradski and A. Kaehler, Learning Open CV: Computer Vision with the Open CV Library, (O’Reilly, 2008).

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge, 2004).

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing (Cambridge, 2007).

The Blender Foundation, “Blender user manual,” 2013, http://wiki.blender.org/index.php/Doc:2.6/Manual .

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (13)

Fig. 1.
Fig. 1.

Flowchart of the automatic merging of 3D DIC data; CA with indexes—are vectors of coordinates of the CA markers, PC—are point clouds, and T3D is an estimated transformation between consecutive data sets.

Fig. 2.
Fig. 2.

Example pair of images acquired during laboratory test of the merging procedure with overlaid CA markers positions: (a) left camera and (b) right camera.

Fig. 3.
Fig. 3.

Visualization of the forward remapping function.

Fig. 4.
Fig. 4.

Example of the sequential stages of the merging procedure: (a) and (b) is a reference pair of images, (c) and (d) is a pair of images from another data set merged with the reference pair. The AOI for merging procedure has been overlaid on the reference pair.

Fig. 5.
Fig. 5.

Model of 3D DIC setup developed in Blender.

Fig. 6.
Fig. 6.

Numerical model of the specimen with overlaid “hook” points P1 and P2.

Fig. 7.
Fig. 7.

Example (a) U and (b) W displacement maps with overlaid points of analysis.

Fig. 8.
Fig. 8.

Distribution of errors within AOI: (a) U displacement measurement: RMS=0.002mm and (b) W displacement measurement: RMS=0.0083mm. Images were obtained after merging of data series 1.

Fig. 9.
Fig. 9.

Distribution of errors within AOI: (a) U displacement measurement: RMS=0.0035mm and (b) W displacement measurement: RMS=0.0054mm. Images were obtained after merging of data series 11.

Fig. 10.
Fig. 10.

Validation arrangement of 3D DIC with automatic merging of data procedure.

Fig. 11.
Fig. 11.

Flowchart of the validation procedure carried out in laboratory conditions.

Fig. 12.
Fig. 12.

δU, δV and δW error maps for linear tension: load 6 kN and 3D DIC configuration 2.

Fig. 13.
Fig. 13.

δU, δV and δW error maps for pushing-out, load 2 and 3D DIC configuration 4.

Tables (5)

Tables Icon

Table 1. Parameters of the 3D DIC System in Each Modeled Positions of the Cameras

Tables Icon

Table 2 Parameters of the Specimen in Each Load State

Tables Icon

Table 3. Results of the 3D DIC Analysis of the Reference Data Set

Tables Icon

Table 4. Errors Obtained from the Analysis of Data Series 4 in Three Selected Load States

Tables Icon

Table 5. Results of Validation Measurements of the Merging Procedure

Equations (11)

Equations on this page are rendered with MathJax. Learn more.

f(T3D)=i=0k[dist(CAref3Di,T3D*CAref3Di)],
M[m,n]=U[m,m]I[m,n]V[n,n].
Hc=i=0k[CAref3Dicentroidref)(CAimg3Dicentroidimg)T].
[U,I,V]=SVD(Hc).
R=VUT
t=Rxcentroidref+centroidimg.
PC3D=T3D*PC3D.
T3Derror=|i=0k[(xixi)2+(yiyi)2+(zizi)2]|/k,
P1error=|i=0k[(xp1ixp1i)2+(yp1iyp1i)2]|/k,
P2error=|i=0k[(xp2ixp2i)2+(yp2iyp2i)2]|/k,
δUPi=|(gUg)/g(hUrefh)/h|,δVPi=|(gVg)/g(hVrefh)/h|,andδWPi=|(gWg)/g(hWrefh)/h|,

Metrics