ISSN 3041-1815. Physicochemical Mechanics of Materials. 2025.
Volume 61, Issue 6
Method of digital processing of deformed surface interferograms for estimating Poisson’s ratio
Keywords
surface interferogram, speckle interferogram, Poisson’s ratio, image proces¬sing, segmentation, Retinex.
Cite as
Ivasenko I. B., Berehulyak O. R., Vorobel R. A., Voronyak T. I., and Stasyshyn I. V. Method of digital processing of deformed surface interferograms for estimating Poisson’s ratio. Physicochemical Mechanics of Materials. 2025. 61(6), 099-103.
https://doi.org/10.15407/pcmm2025.06.099
Abstract
An automated method for estimating the Poisson’s ratio using interferograms and speckle interferograms of the material surface by means of digital image processing was developed. Preliminary image processing based on a parameterized retinex was performed to equalize the background in preparation for further segmentation. Image segmentation was carried out using a threshold level, that maximizes the dispersion between two classes. The Poisson coefficient was estimated based on the angle between the asymptotes of the hyperbolas of interference fringes obtained by averaging the edge points of the segmentation results. The method was tested on interferograms of the steel beam surface, obtained under different loads. The application of the method to difference electronic speckle pattern interferogram of the beam surface made of aluminum alloy is demonstrated. The results of experimental studies demonstrate the advantages of the proposed method.
References
- N. G. Greaves, “Poisson’s ratio over two centuries: challenging hypotheses,” Notes and Records of the Royal Society, 67, Is. 1, 37-58 (2013). https://doi.org/10.1098/rsnr.2012.0021
- S. Timoshenko, and J. N. Goodier, Theory of Elasticity, McGraw Hill Education, Columbus (2017).
- A. R. Ganesan, “Measurement of poisson’s ratio using real-time digital speckle pattern interferometry,” Optics and Lasers in Eng., 11, Is. 4, 265-269 (1989). https://doi.org/10.1016/0143-8166(89)90064-X
- G. Romero, G. Gonza, E. Alanís, and C. Martínez, “Poisson’s ratio determination by digital holographic interferometry,” Optica Pura y Aplicada, 44, Is. 1, 197-205 (2011).
- M. Kumar, K. Gaur, and Ch. Shakher, “Measurement of material constants (Young’s modulus and Poisson’s ratio) of polypropylene using digital speckle pattern interferometry (DSPI),” J. of Japanese Society of Experimental Mechanics, 15, 87-91 (2015).
- M. Luceadams, M. Steinzig, and A. Abdelkefi, “Parametric estimation of Poisson’s ratio for thin hinged-hinged plates,” Europ. J. of Mechanics, A/Solids, 99 (2023). Art. no. 104936. https://doi.org/10.1016/j.euromechsol.2023.104936
- M. Luceadams, M. Steinzig, A. Abdelkefi, and D. Mascareñas, “The estimation of Poisson’s ratio by time-averaging and Cornu’s method for isotropic beams,” Mech. Syst. and Signal Process, 189, (2023). Art. no. 110077. https://doi.org/10.1016/j.ymssp.2022.110077
- M. Luceadams, M. Steinzig, and A. Abdelkefi, “A unified expression for estimating Poisson’s ratio from a hinged-hinged beam with a use for abnormality detection,” Mech. Syst. and Signal Process, 213 (2024). Art. no. 111322. https://doi.org/10.1016/j.ymssp.2024.111322
- L. Muravsky, A. Kmet’, and T. Voronyak, “Two approaches to the blind phase shift extraction for two-step electronic speckle pattern interferometry,” Opt. Eng., 52, Is. 10 (2023). Art. no. 101909. https://doi.org/10.1117/1.OE.52.10.101909
- T. I. Voronyak, “Determination of Poisson’s ratio by the methods of two-step phase-shifting interferometry,” Mater. Sci., 49, Is. 4, 508-515 (2014). https://doi.org/10.1007/s11003-014-9643-5
- R. Jones, and C. Wykes, Holographic and Speckle Interferometry, Cambridge University Press, Cambridge (1989). https://doi.org/10.1017/CBO9780511622465
- S. Rustagi, T. Tuteja, V. Sharma, V. Gangwar, and A. S. Parihar, “Comparative study of various image enhancement techniques based on Retinex theory and fuzzy logic,” in Second Int. Conf. on Electronics, Communication and Aerospace Technology (ICECA) (Coimbatore, India, 2018), pp. 464-469. https://doi.org/10.1109/ICECA.2018.8474787
- R. Vorobel, I. Ivasenko, and O. Berehulyak, “Automatized computer system for evaluation of rust using modified single-scale retinex,” in IEEE First Ukraine Conf. on Electrical and Computer Engineering (UKRCON) (Kyiv, Ukraine, 2017), pp. 1002-1006. https://doi.org/10.1109/UKRCON.2017.8100401
- X. Xu, S. Xu, L. Jin, and E. Song, “Characteristic analysis of Otsu threshold and its applications,” Pattern Recognition Letters, 32, Is. 7, 956-961 (2011). https://doi.org/10.1016/j.patrec.2011.01.021
- P. Yang, W. Song, X. Zhao, R. Zheng, and L. Qingge, “An improved Otsu threshold segmentation algorithm,” Int. J. of Comput. Sci. and Eng., 22, Is. 1, 146-153 (2020). https://doi.org/10.1504/IJCSE.2020.107266
- C. Huang, X. Li, and Y. Wen, “An Otsu image segmentation based on fruitfly optimization algorithm,” Alexandria Eng. J., 60, Is. 1, 183-188 (2021). https://doi.org/10.1016/j.aej.2020.06.054