Application of thermal tomography method for detection of objects immersed in the ground

Sergiy I. Melnyk, Serhii S. Melnyk, Gennadiy Fedorenko, Vyacheslav Kharchenko, Volodymyr Kokhanovskyi

Abstract


The subject matter of the article is the processes of propagation of thermal waves excited by daily solar activity in soil with local inhomogeneities (inclusions). The goal is to develop a mathematical model of these processes and algorithms for detecting and identifying these inhomogeneities against a background of high-level structural and instrumental noise. The tasks to be solved are: to analyze the state of developments in thermal tomography of the soil and the detection of objects hidden within it; to build a numerical-analytical model of the propagation of thermal waves in soil with inclusions under model and full-scale experimental conditions; to develop an algorithm for compensating artifacts caused by the inhomogeneity of soil emissivity distribution, and an algorithm for suppressing instrument noise based on the criterion of minimizing the loss of information about inclusion parameters; and to analyze the adequacy of the developed models and the effectiveness of the algorithms in a computer experiment. The methods used include thermal conductivity theory, information theory, numerical modeling using the COMSOL MULTIPHISICS software package. The following results were obtained: The main obstacles to the widespread use of the thermal tomography method are structural noise associated with the inhomogeneity of surface emissivity (particularly in soil). Typically, the ratio of the depth of the object to its characteristic size is considered to be 1/3. Two algorithms have been developed for restoring information lost due to the presence of noise, which enable an order-of-magnitudeimprovement in the efficiency of the thermal method. The first algorithm effectively reduces the level of structural noise, and the second reduces the noise of the thermal imager matrix. Their combination allows obtaining a clear image of the subsoil even with 50% structural and 200 mK instrumental noise at a depth criterion value of 3/2. These preliminary conclusions were confirmed in a computer model of thermal imaging measurements of an object immersed in the subsoil using a passive control method (driven by daily solar activity). Several features that could theoretically affect the efficiency of the algorithms in a real experiment were analyzed. Conclusions: the scientific novelty of the results obtained is as follows: a new method of thermal tomography of soil inhomogeneities has been developed, which is based on an algorithm for comparing two thermograms of the soil surface, taken at fixed points in time dependent on meteorological conditions during the day, and a combination of two algorithms for processing these thermograms, which enable the elimination of artifacts caused by structural noise and suppression of instrumental noise with minimal loss of useful information about the inhomogeneity.

Keywords


thermal tomography; noise filtering; thermal imaging soil monitoring; thermographic data

References


Fedorenko, G., Fesenko, H., & Kharchenko, V. Analiz metodiv i rozroblennya kontseptsiyi harantovanoho vyyavlennya ta rozpiznavannya vybukhonebezpechnykh predmetiv [Analysis of methods and development of the concept of guaranteed detection and recognition of explosive objects]. Suchasnyy stan naukovykh doslidzhenʹ ta tekhnolohiy v promyslovosti – Innovative Technologies and Scientific Solutions for Industries, 2022, no. 4 (22), pp. 20-31. DOI: 10.30837/ITSSI.2022.22.020. (In Ukrainian).

Yeom, S. Thermal Image Tracking for Search and Rescue Missions with a Drone. Drones, 2024, vol. 8, no. 2, article no. 53. DOI: 10.3390/drones8020053.

Fedorenko, G., Fesenko, H., Kharchenko, V., Kliushnikov, I., & Tolkunov, I. Robotic-biological systems for detection and identification of explosive ordnance: concept, general structure, and models. Radioelectronic and Computer Systems. 2023, no. 2, pp. 143-159. DOI: 10.32620/reks.2023.2.12.

Heifetz, A., Shribak, D., Zhang, X., Saniie, J., L. Fisher, Z., Liu, T., Sun, J. G., Elmer, T., Bakhtiari, S., & Cleary, W. Thermal tomography 3D imaging of additively manufactured metallic structures. AIP Advances, 2020, vol. 10, iss. 10, article no. 105318. DOI: 10.1063/5.0016222.

Thanh, N. T., Sahli, H., & Hao, D. N. Infrared Thermography for Buried Landmine Detection: Inverse Problem Setting. IEEE Transactions on Geoscience and Remote Sensing, 2008, vol. 46, no. 12, pp. 3987-4004. DOI: 10.1109/TGRS.2008.2000926.

Wong, B. S., Tui, C. G., Bai, W., Tan, P. H., Low, B. S., & Tan K. S. Thermographic Evaluation of Defects in Composite Materials. Non-Destructive Testing and Condition Monitoring, 1999, vol. 41, no. 8, p. 504.

Hrytsyk, V. V., & Zadorozhnyi, V. I. Doslidzhennya teoriyi zobrazhenʹ: poperednya obrobka – vydilennya krayiv [Research of image theory: preprocecion – edge detectors]. Prykladni pytannya matematychnoho modelyuvannya –Applied questions of mathematical modelling, 2023, no 1, pp. 20–29. DOI: 10.32782/mathematical-modelling/2023-6-1-2 (In Ukrainian).

Sedeeq, I. Image Forgery Detection Using Histogram-Oriented Gradients (HOG). Iraqi Journal of Science, 2025, vol. 66, no 5, pp. 2048-2058. DOI: 10.24996/ijs.2025.66.5.22.

Stankevych, S. A., Kondratov, O. M., Herda, M. I., Maslenko, O. V., & Saprykin, Ye. Yu. Iteratyvne pokrashchennya infrachervonykh zobrazhenʹ u chastotniy oblasti [Iterative enhancement of infrared images in the frequency domain]. Visti vyshchykh uchbovykh zakladiv. Radioelektronika – Visnyk of Higher Educational Institutions. Radioelectronics, 2024, vol. 67, no 6, pp. 311-322. DOI: 10.20535/S0021347024070045. (In Ukrainian).

Li, H., Wang, S., Li, S., Wang, H., Wen, S., & Li, F. Thermal Infrared-Image-Enhancement Algorithm Based on Multi-Scale Guided Filtering. Fire. 2024, vol. 7, iss. 6, article no. 192. DOI: 10.3390/fire7060192.

Gagnon, M.-A., Lagueux, P., Gagnon, J.-P., Savary, S., Tremblay, P., Farley, V., Guyot, E., & Chamberland, M. Airborne Thermal Infrared Hyperspectral Imaging of Buried Objects. SPIE Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, Baltimore, 2015, vol. 9454, article no. 94540K. DOI: 10.1117/12.2177182.

Zhang, X., Liu, C., Chen, R., Zeng, B., Xiong, H., Wang, K., & Zhao, S. Improvement of Temperature and Emissivity Separation Algorithm for Thermal Infrared Hyperspectral Imaging Based on Airborne Data. IEEE Transactions on Geoscience and Remote Sensing. 2024, vol. 63, pp. 1-15. DOI: 10.1109/TGRS.2024.3520865.

Deniz, M., Seçkin, M., Gençer, Ç. & Koç, D. Infrared Thermography Image Based Classification of Soil Dirt and Fabric. International Journal of 3D Printing Technologies and Digital Industry. 2023, vol. 7, iss. 3, pp. 441-455. DOI: 10.46519/ij3dptdi.1339049.

Wu, X., Hong, D., & Chanussot, J. UIU-Net: U-Net in U-Net for Infrared Small Object Detection. IEEE Transactions on Image Processing. 2023, vol. 32, pp. 364–376. DOI: 10.1109/TIP.2022.3228497.

Melnyk, S. I., Petrychenko, H. I., & Tuluzov, I. H. Metrolohichni aspekty vymiryuvanʹ u zadachakh teplovoyi tomohrafiyi [Metrological aspects of measurements in thermal tomography problems]. Metrolohiya ta prylady – Metrology and Instruments, 2017, vol. 67, no 5, pp. 38–47. (In Ukrainian).

Melnyk, S., Petrychenko, H., & Tuluzov, I. Novi metody teplovoyi tomohrafiyi, a takozh filʹtratsiyi teploviziynykh zobrazhenʹ [New methods of thermal tomography and filtering of thermographic images]. Vymiryuvalʹna tekhnika ta metrolohiya – Measurement Technology and Metrology, 2016, vol. 77, pp. 48–57. (In Ukrainian).

Ledwon, D., Sage, A., Juszczyk, J. & Badura, P. Tomographic reconstruction from planar thermal imaging using convolutional neural network. Scientific Reports, 2022, vol. 12, article no. no. 2347. DOI: 10.1038/s41598-022-06076-z.

Melnyk, S. I., Diakoniuk, L., Kukharskyi, V., & Savula, Ya. Matematychne modelyuvannya protsesiv teploprovidnosti u bahatosharovykh seredovyshchakh iz tonkymy vklyuchennyamy [Mathematical Modeling of Heat Conduction Processes in Multilayer Media with Thin Inclusions]. Matematychni problemy mekhaniky neodnoridnykh struktur – Mathematical Problems of the Mechanics of Inhomogeneous Structures, 2000, vol. 1, pp. 212–215. (In Ukrainian).

Melnyk, S. I., Melnyk, S. S., & Tuluzov, I. G. Method of projection dynamic thermal tomography (PDTT). 11 International Conference on Quantitative Infrared Thermography: QIRT-2012, Naples, 2012, pp. 1-6. DOI: 10.21611/qirt.2012.308.




DOI: https://doi.org/10.32620/aktt.2025.5.06