Ga-Based Laser Speckle Pattern Digital Image Correlation Method for Surface Strain Measurements

Ga-Based Laser Speckle Pattern Digital Image Correlation Method for Surface Strain Measurements

Arka Das Eduardo Divo Faisal Moslehy Alain Kassab

Mechanical Engineering Department, Embry-Riddle Aeronautical University, USA

Mechanical and Aerospace Engineering Department, University of Central Florida, USA

Available online: 
| Citation

© 2020 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (



This article introduces an innovative technique that integrates a genetic algorithm (GA)-based digital image correlation with laser speckle photography for the estimation of surface displacements in struc- tures. The images (before and after deformation) are digitized using a digital camera, and the grayscale intensity matrices are read and processed by an image processing algorithm. The two matrices of the images are then inputted into GA-based optimizer that utilizes an advanced cross-correlation fitness function to approximate the surface displacements. Furthermore, the surface strains are computed from the displacements using radial basis function differentiation and interpolation. The computed displacements are compared with simulated results obtained by the boundary element method. Close agreement between the two results proves the validity of the developed noncontact technique for accurately estimating surface displacements and strains. These experimentally estimated displacements can further be used in an inverse technique to detect and characterize subsurface cavities in structures.


boundary element method, genetic algorithm, laser speckle pattern, RBF interpolation, surface strain


[1] Manthey, D.W. & Lee, D., Vision based Surface Strain Measurement System. JOM,47(7), pp. 46–49, 1995.

[2] Vogel, J.H., & Lee, D., The automated measurement of strain from three-dimensionaldeformed surfaces. JOM, 42(2), pp. 8–13, 1990.

[3] Theocaris, P.S., Moire Fringes in Strain Analysis, Oxford: Pergamon Press, 1969.

[4] Durelli, A.J. & Parks, V.J., Moire Analysis of Strain, Prentice-Hall, 1970.

[5] Chiang, F.P., Experimental Stress Analysis Techniques SESA Monograph, edited byA.S. Kobayashi, Chap.6, 1978

[6] Vest, C.M., Holographic Interferometry, John Wiley and Sons, 1979.

[7] Erf, R.K., Speckle Metrology, Academic Press, New York, 1978.

[8] Kobayashi, A.S., Handbook on experimental Mechanics, VCH Publishers, New York,1993.

[9] Dainty, J.C., Laser Speckle and Related Phenomena, Springer-Verlag, New York, 1975

[10] Takaki, T., et al., Strain visualization sticker using Moiré fringe for remote sensing,Proceeding of the sixth international conference on bridge maintenance, safety andmanagement, pp. 8–12, 2012.

[11] Han, B., Higher sensitivity moiré interferometry for micromechanical studies. OpticalEngineering, 31(7), pp. 1517–1526, 1992. 14: Strains components e e g x , y ,and xy distribution obtained by radial basis functioninterpolation.

[12] Huntley, J. M., Palmer, S.J.P., Goldrein, H. T. & Melin, L.G., Microstructural strainanalysis by high magnification moiré interferometry. SPIE Proceedings (2545) (InterferometryVII: Applications), San Diego, USA, pp. 86–95, 1995.

[13] Trolinger, J.D., Fundamentals of Interferometry and Holography for Civil andStructural Engineering Measurements. Optics and Lasers in Engineering, 24(2–3),pp. 89–109, 1996.

[14] Rastogi, P. (ed.), Photomechanics, Springer-Verlag: Berlin Heidelberg, pp. 103–145, 2000.

[15] Francis, D., Tatam, R.P. & Groves, R.M., Shearography technology and application: areview. Measurement Science and Technology, 21(10), pp. 102001–102030.

[16] Sutton, M.A., & Wolters, W.J., Determination of displacement using an improveddigital image correlation method, Image Vision Computing, 1(3), pp. 133–139, 1983.

[17] Chu, T.C., Ranson, W.F., Sutton, M.A, & Peters, W.H., Application of digital image correlationtechniques to experimental mechanics, Experimental Mechanics, 25, pp. 232–244,1985.

[18] Sutton, M. A., Orteu, J.J., Schreier, H., Image Correlation for Shape, Motion and DeformationMeasurements. Springer-Verlag: US, pp.

[19] Bing, P., Hui-min, X., Bo-qin, X., Fu-long, D., Performance of sub-pixel registrationalgorithms in digital image correlation. Measurement Science and Technology, 17(6),pp. 1615–1621, 2006.

[20] Mudassar, A.A., Butt, S., Improved Digital Image Correlation method. Optics andLasers in Engineering, 87, pp. 156–167, 2016.

[21] Zhang, D.S., Luo, M., Arola, D.D., Displacement/strain measurements using an opticalmicroscope and digital image correlation. Optical Engineering, 45(3), 2006.

[22] Sutton, M.A, Li, N., Joy, D.C. & Reynolds, A.P., Scanning electron microscopy forquantitative small and large deformation measurements Part I: SEM imaging at magnificationsfrom 200 to 10,000. Experimental Mechanics, 47, pp. 775–787, 2007.

[23] Yoneyama, S., Kikuta, H., Kitagawa, A. & Kitamura, K., Lens distortion correction fordigital image correlation by measuring rigid body displacement. Optical Engineering,45(2), 2006.

[24] Sutton, M.A., et al., Metrology in a scanning electron microscope: Theoretical developmentsand experimental validation. Measurement Science and Technology, 17(10),pp. 2613–2622, 2006.

[25] Sutton, M.A., et al., Scanning electron microscope for quantitative small and largedeformation measurements part II, Experimental validation for magnifications from 200to 10,000. Experimental Mechanics, 47(6), pp. 789–804, 2007.

[26] Sun, Y. & Pang, J.H.L., AFM image reconstruction for deformation measurementsby digital image correlation. Nanotechnology, 17(4), pp. 933–939, 2006.

[27] Gauvin, C., Jullien, D., Doumalin, P., Dupre, J.C. & Gril, J., Image correlation to evaluatethe influence of hygrothermal loading on wood. Strain, 50, pp. 428–435, 2014.

[28] Pan, B., Reliability-guided digital image correlation for image deformation measurement.Applied Optics, 48(8), pp. 1535–1542, 2009.

[29] Yang, X., Liu, Z. & Xie, H., A real time deformation evaluation method for surface andinterface of thermal barrier coatings during 1100 °C thermal shock. Measurement Scienceand Technology, 23(10), pp. 105604–105614, 2012.

[30] Brillaud, J. & Lagattu, F., Limits and possibilities laser speckle and white-light imagecorrelationmethods: Theory and experiments. Applied Optics, 41(31), pp. 6603–6613,2002.

[31] Song, J., Yang, J., Liu, F. & Lu, K., Quality assessment of Laser speckle patterns fordigital image correlation by a Multi Factor Fusion Index. Optical Engineering, 124,pp. 105822–105837, 2020.

[32] Goodman, J.W., Laser speckle and related phenomena. Statistical Properties of LaserSpeckle Patterns, 9, pp. 9–75, 1975.

[33] Kassab, A.J., Moslehy, F.A. & Daryapurkar, A., Detection of cavities by an inverse elastostaticsboundary element method: experimental results. Transactions of Modellingand Simulation, 8, pp. 85–92, 1994.

[34] Fraley, J.E., Hamed, M.A., Peters, W.H. & Ranson, W.F., Experimental boundaryintegral equation application in speckle interferometry. SESA Spring Conference,pp. 68–71, 1981.

[35] Peters, W.H. & Ranson, W.F., Digital imaging techniques in experimental stress analysis.Optical Engineering, 21, pp. 427–431, 1982.

[36] Pilch, A., Maudlin, J., Mahajan, A. & Chu, T., Intelligent image correlation using geneticalgorithms for measuring surface displacements and strain profiles. ASME InternationalMechanical Engineering Congress and Exposition, DSC-Volume 70, pp. 81–88, 2001.

[37] Chu. T., Mahajan, A. & Liu, C.T., An economical vision-based method to obtain allfielddeformation profiles. Experimental Techniques, 26(6), pp. 25–29.

[38] Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning.Addison-Wesley, Reading, MA, 1989.

[39] Divo, E.A., Kassab, A.J. & Rodríguez, F., An efficient singular superposition techniquefor cavity detection and shape optimization. Numerical Heat Transfer, Part B: Fundamentals,46(1), pp. 1–30, 2004.

[40] Divo, E., Kassab, A. & Rodriguez, F., Characterization of space dependent thermalconductivity with a BEM based Genetic Algorithm. Numerical Heat Transfer, Part A:Applications, 37(8), pp. 845–875, 2000.

[41] Silieti, M., Divo, E., & Kassab, A.J., Singular superposition/boundary element methodfor reconstruction of multi-dimensional heat flux distributions with applications to filmcooling holes. Computers, Materials and Continua, 12(2), pp. 121–144, 2009.

[42] Hardy, R.L., Multiquadric equations of topography and other irregular surfaces. Journalof Geophysical Research, 76(8), pp. 1905–1915, 1971.

[43] Buhmann, M.D., Radial Basis Functions: Theory and Implementation. Cambridge UniversityPress, Cambridge, 2003.

[44] Kansa, E.J., Hon, Y.C., Circumventing the ill-conditioning problem with multiquadricradial basis functions: Applications to elliptical partial differential equations. Computers& Mathematics with Applications, 39(7–8), pp. 123–137, 2000.

[45] Pepper, D., Kassab, A. & Divo, E., (eds.), Introduction to Finite Element, BoundaryElement and meshless methods: With Applications to Heat Transfer and Fluid Flow,ASME Press.

[46] Sarler, B., Tran-Cong, T. & Chen, C.S., Meshfree direct and indirect local radial basisfunction collocation formulations for transport phenomena. WIT transactions on Modellingand Simulation, pp. 417–427, 2005.

[47] Brebbia, C.A., Telles, J.C.F. & Wrobel, L.C. (eds.), Boundary Element Techniques.Springer-Verlag: Berlin; 1984.

[48] Gamez, B., Ojeda, D., Divo, E., Kassab, A. & Cerrolaza, M., Parallelized iterativedomain decomposition boundary element method for thermoelasticity in piecewisenon-homogeneous media. Engineering Analysis with Boundary Elements, 32,pp. 1061–1073, 2008.

[49] Ojeda, D., Gamez, B., Divo, E., Kassab, A. & Cerrolaza, M., Singular superpositionelastostatics BEM/GA algorithm for cavity detection. Boundary Elements and OtherMesh Reduction Methods XXIX, 44, pp. 313–322, 2007.