Abstract

This paper presents simulation of speckle activity through controlling a moving plate. We present two procedures to extract the initial movement frequency and amplitude, either through correlation calculus or through processing the temporal history of the speckle pattern. We compare and discuss these two methods in terms of efficiency and the ability to retrieve motion parameters. The correlation technique seems to be more suitable for monitoring biospeckle activity as it provides more reliable parameter estimation than the temporal history of the speckle pattern. The evolution of temporal history of the speckle pattern parameters and their response sensibility with amplitude and frequency variations have been studied and quantified. Briers contrast appears to depend only on movement amplitude, whereas inertia moment varies with amplitude and frequency.

© 2013 Optical Society of America

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References

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  1. H. Rabal and R. Braga, “Dynamic speckle, origin and features,” in Dynamic Laser Speckle and Applications (CRC, 2008).
  2. R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
    [CrossRef]
  3. R. Nassif, F. Pellen, C. Magné, B. Le Jeune, G. Le Brun, and M. Abboud, “Scattering through fruits during ripening: laser speckle technique correlated to biochemical and fluorescence measurements,” Opt. Express 20, 23887–23897 (2012).
    [CrossRef]
  4. M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
    [CrossRef]
  5. G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
    [CrossRef]
  6. J. D. Briers, “Laser speckle contrast imaging for measuring blood flow,” Opt. Appl. 37, 139–156 (2007).
    [CrossRef]
  7. J. D. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1, 174–179 (1996).
    [CrossRef]
  8. P. Zakharov, A. Völker, M. Wyss, F. Haiss, N. Calcinaghi, C. Zunzunegui, A. Buck, F. Scheffold, and B. Weber, “Dynamic laser speckle imaging of cerebral blood flow,” Opt. Express 17, 13904–13917 (2009).
    [CrossRef]
  9. A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).
  10. R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
    [CrossRef]
  11. G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
    [CrossRef]
  12. A. Zdunek and J. Cybulska, “Relation of biospeckle activity with quality attributes of apples,” Sensors 11, 6317–6327 (2011).
    [CrossRef]
  13. T. L. Alexander, J. E. Harvey, and A. R. Weeks, “Average speckle size as a function of intensity threshold level: comparison of experimental measurements with theory,” Appl. Opt. 33, 8240–8250 (1994).
    [CrossRef]
  14. G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).
  15. C. E. Shannon, “Communication in the presence of noise,” Proc. IRE 37, 10–21 (1949).
  16. J. D. Briers, “The statistics of fluctuating speckle patterns produced by a mixture of moving and stationary scatterers,” Opt. Quantum Electron. 10, 364–366 (1978).
    [CrossRef]
  17. R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
    [CrossRef]
  18. Z. Zalevsky, Y. Beiderman, I. Margalit, S. Ginglod, M. Teicher, V. Mico, and J. Garcia, “Simultaneous remote extraction of multiple speech sources and heart beats from secondary speckles pattern,” Opt. Express 17, 21566–21580 (2009).
    [CrossRef]

2012 (1)

2011 (1)

A. Zdunek and J. Cybulska, “Relation of biospeckle activity with quality attributes of apples,” Sensors 11, 6317–6327 (2011).
[CrossRef]

2009 (3)

2007 (3)

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

J. D. Briers, “Laser speckle contrast imaging for measuring blood flow,” Opt. Appl. 37, 139–156 (2007).
[CrossRef]

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

2005 (1)

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

2003 (1)

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

1999 (1)

R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
[CrossRef]

1996 (1)

J. D. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1, 174–179 (1996).
[CrossRef]

1994 (1)

1978 (1)

J. D. Briers, “The statistics of fluctuating speckle patterns produced by a mixture of moving and stationary scatterers,” Opt. Quantum Electron. 10, 364–366 (1978).
[CrossRef]

1973 (1)

R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
[CrossRef]

1949 (1)

C. E. Shannon, “Communication in the presence of noise,” Proc. IRE 37, 10–21 (1949).

Abboud, M.

Alanïs, E. E.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Alexander, T. L.

Arizaga, R.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
[CrossRef]

Baldwin, G.

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

Beiderman, Y.

Braga, R.

H. Rabal and R. Braga, “Dynamic speckle, origin and features,” in Dynamic Laser Speckle and Applications (CRC, 2008).

Braga, R. A.

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Braga Junior, R. A.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Briers, J. D.

J. D. Briers, “Laser speckle contrast imaging for measuring blood flow,” Opt. Appl. 37, 139–156 (2007).
[CrossRef]

J. D. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1, 174–179 (1996).
[CrossRef]

J. D. Briers, “The statistics of fluctuating speckle patterns produced by a mixture of moving and stationary scatterers,” Opt. Quantum Electron. 10, 364–366 (1978).
[CrossRef]

Broglia, V. G.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Buck, A.

Calcinaghi, N.

Cap, N.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

Costa, R.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Cybulska, J.

A. Zdunek and J. Cybulska, “Relation of biospeckle activity with quality attributes of apples,” Sensors 11, 6317–6327 (2011).
[CrossRef]

De Velis, J. B.

G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).

Dinstein, I.

R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
[CrossRef]

Enes, A. M.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Fabbro, I. M.

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Frankevych, L.

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

Garcia, J.

Ginglod, S.

Haiss, F.

Haralick, R. M.

R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
[CrossRef]

Harvey, J. E.

Horgan, G.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

ïlvarez, L.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Konstankiewicz, K.

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

Le Brun, G.

Le Jeune, B.

Magné, C.

Margalit, I.

Martinez, C. C.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Mico, V.

Muravsky, L.

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

Nassif, R.

Pajuelo, M.

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

Pellen, F.

Porrent, G. B.

G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).

Rabal, H.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
[CrossRef]

H. Rabal and R. Braga, “Dynamic speckle, origin and features,” in Dynamic Laser Speckle and Applications (CRC, 2008).

Rabal, H. J.

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Rabelo, G.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Rabelo, G. F.

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Reynolds, G. O.

G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).

Romero, G. G.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Salazar, G. A.

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

Scheffold, F.

Shanmugam, K.

R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
[CrossRef]

Shannon, C. E.

C. E. Shannon, “Communication in the presence of noise,” Proc. IRE 37, 10–21 (1949).

Silba, B.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Teicher, M.

Thompson, B. J.

G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).

Trivi, M.

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
[CrossRef]

Trivi, M. R.

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Völker, A.

Weber, B.

Webster, S.

J. D. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1, 174–179 (1996).
[CrossRef]

Weeks, A. R.

Wyss, M.

Zakharov, P.

Zalevsky, Z.

Zdunek, A.

A. Zdunek and J. Cybulska, “Relation of biospeckle activity with quality attributes of apples,” Sensors 11, 6317–6327 (2011).
[CrossRef]

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

Zunzunegui, C.

Appl. Opt. (1)

Biosyst. Eng. (1)

G. G. Romero, C. C. Martinez, E. E. Alanïs, G. A. Salazar, V. G. Broglia, and L. ïlvarez, “Bio-speckle activity applied to the assessment of tomato fruit ripening,” Biosyst. Eng. 103, 116–119 (2009).
[CrossRef]

IEEE Trans. Syst. Man Cybern. (1)

R. M. Haralick, K. Shanmugam, and I. Dinstein, “Textural features for image classification,” IEEE Trans. Syst. Man Cybern. 3, 610–621 (1973).
[CrossRef]

Int. Agrophys. (1)

A. Zdunek, L. Muravsky, L. Frankevych, and K. Konstankiewicz, “New nondestructive method based on spatial-temporal speckle correlation technique for evaluation of apples quality during shelf-life,” Int. Agrophys. 21, 305–310 (2007).

J. Biomed. Opt. (1)

J. D. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1, 174–179 (1996).
[CrossRef]

Opt. Appl. (1)

J. D. Briers, “Laser speckle contrast imaging for measuring blood flow,” Opt. Appl. 37, 139–156 (2007).
[CrossRef]

Opt. Express (3)

Opt. Laser Technol. (1)

R. Arizaga, M. Trivi, and H. Rabal, “Speckle time evolution characterization by the co-occurrence matrix analysis,” Opt. Laser Technol. 31, 163–169 (1999).
[CrossRef]

Opt. Lasers Eng. (2)

M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, “Bio-speckle assessment of bruising in fruits,” Opt. Lasers Eng. 40, 13–24 (2003).
[CrossRef]

R. A. Braga Junior, B. Silba, G. Rabelo, R. Costa, A. M. Enes, N. Cap, H. Rabal, R. Arizaga, M. Trivi, and G. Horgan, “Reliability of biospeckle image analysis,” Opt. Lasers Eng. 45, 390–395 (2007).
[CrossRef]

Opt. Quantum Electron. (1)

J. D. Briers, “The statistics of fluctuating speckle patterns produced by a mixture of moving and stationary scatterers,” Opt. Quantum Electron. 10, 364–366 (1978).
[CrossRef]

Proc. IRE (1)

C. E. Shannon, “Communication in the presence of noise,” Proc. IRE 37, 10–21 (1949).

Rev. Bras. Eng. Agríc. Ambient. (1)

G. F. Rabelo, R. A. Braga, I. M. Fabbro, M. R. Trivi, H. J. Rabal, and R. Arizaga, “Laser speckle techniques in quality evaluation of orange fruits,” Rev. Bras. Eng. Agríc. Ambient. 9, 570–575 (2005).
[CrossRef]

Sensors (1)

A. Zdunek and J. Cybulska, “Relation of biospeckle activity with quality attributes of apples,” Sensors 11, 6317–6327 (2011).
[CrossRef]

Other (2)

G. O. Reynolds, J. B. De Velis, G. B. Porrent, and B. J. Thompson, Physical Optics Notebook: Tutorials in Fourier Optics (SPIE, 1989).

H. Rabal and R. Braga, “Dynamic speckle, origin and features,” in Dynamic Laser Speckle and Applications (CRC, 2008).

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Figures (6)

Fig. 1.
Fig. 1.

Top view of the experimental setup. λ/2 is a half-wave plate, and LFG is a low frequency generator.

Fig. 2.
Fig. 2.

For a 20 mHz and 1000 mV movement of the aluminum plate, (a) speckle image correlation C(t) as function of time and (b) THSP horizontal cut.

Fig. 3.
Fig. 3.

(a) Aluminum plate displacement as a function of the imposed sinusoidal signal amplitude for two frequency values: Fm=40mHz (solid line) and 80 mHz (dashed line). (b) Calculated frequency using correlation plots versus imposed frequency for the aluminum plate and for both amplitudes: 100 mV (solid line) and 500 mV (dashed line).

Fig. 4.
Fig. 4.

Speckle image decorrelation ΔC as a function of the plate displacement for two frequency values: Fm=40mHz (solid line) and 80 mHz (dashed line).

Fig. 5.
Fig. 5.

THSP image for a 20 mHz and 1000 mV sinusoidal movement of the aluminum plate.

Fig. 6.
Fig. 6.

Case of the rubber plate: (a) BC variation as a function of frequencies for both amplitudes. (b) BC variation as a function of amplitudes for both frequencies. (c) IM variation as a function of frequencies for both amplitudes. (d) IM variation as a function of amplitudes for both frequencies. Symbols represent experimental values, and error bars are smaller than symbols.

Equations (3)

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

C(t,x,y)=I(t0,x0,y0)I(t,x,y)I(t0,x0,y0)I(t,x,y)[(I2(t0,x0,y0)I(t0,x0,y0)2)(I2((t,x,y))I((t,x,y))2)]1/2
BC=σ2(t)(n)I2.
IM=Mi,j(ij)2,

Metrics