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Infrared Thermography for Land Mine Detection

  • Nguyen Trung Thành
  • Dinh Nho Hào
  • Hichem Sahli
Part of the Advances in Pattern Recognition book series (ACVPR)

Abstract

This chapter introduces the application of infrared (IR) thermography in land mine detection. IR thermography in general and for remotely detecting buried land mines in particular, seems to be a promising diagnostic tool. Due to the difference in thermophysical properties of mines and the soil (mines retain or release heat at a rate different from the soil), soil-surface thermal contrasts above the mines are formed. These contrasts are captured by IR cameras to show the changes in temperature over the mines, which can be used for detecting them. Clearly, the degree of success of such detection technology depends on the factors that affect the formation of the thermal contrasts (signatures), such as the depth of burial; soil properties and attributes, including mine properties (size); as well as the time of day during which the measurement is carried out. Another important factor that strongly influences the viability of IR detection method is the rate of false alarms. Indeed, IR sensors may detect any thermally transmitting objects, not only land mines. It is therefore necessary to develop parameter estimation and decision-making tools that enable the IR technology to distinguish signals resulting from a land mine and unrelated clutter signals. This chapter consists of four sections. The first section introduces the physical principles of IR thermography and gives an overview of its literature. The flowchart of the technique is also given in this section. In the second one, we summarize a thermal model of the soil with the presence of shallowly buried objects. This model is used for studying the influence of soil and land mine properties on the temperature distribution of the soil, especially on its surface. The third section aims at detecting possible anomalies in the soil using IR images and classifying them as mines or nonmine objects. The classification is based on the estimation of the thermal and geometric properties of the detected anomalies. In the fourth section, the performance, in terms of probability of detection and false alarm rates, of the proposed approach for an experimental data set is presented. The processing chain of IR thermography, including data acquisition, data preprocessing, anomaly detection, and estimation of thermal and geometric properties of the detected anomalies, is presented and illustrated using an experimental data set measured in an outdoor minefield. Finally, conclusions on the statistical reliability of the IR technique are drawn.

Keywords

False Alarm Thermal Model Acrylonitrile Butadiene Styrene Infrared Thermography Thermal Contrast 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Chapter's References

  1. 1.
    M. Albert, G. Koh, G. Koenig, S. Howington, J. Peters, and A. Trang. Phenomenology of dynamic thermal signatures around surface mines. In R.S. Harmon, J.T. Broach, and J.H. Holloway Jr., editors, Proceedings of SPIE 5794, Detection and Remediation Technologies for Mine and Minelike Targets X, pages 846–856, 2005Google Scholar
  2. 2.
    O.M. Alifanov. Inverse Heat Transfer Problems. Springer-Verlag, Berlin, 1994zbMATHGoogle Scholar
  3. 3.
    S.R. Arridge. The forward and inverse problems in time resolved infrared imaging. SPIE Medical Optical Tomography Functional Imaging and Monitoring, SPIE-IS11:35–64, 1993Google Scholar
  4. 4.
    B.A. Baertlein and I.K. Sendur. Role of environmental factors and mine geometry in thermal IR mine signatures. In A.C. Dubey, J.F. Harvey, J.T. Broach, and V. George, editors, Proceedings of SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, pages 449–460, 2001Google Scholar
  5. 5.
    B.A. Barbour, S. Kordella, M.J. Dorsett, and B.L. Kerstiens. Mine detection using a polari-metric IR sensor. IEE Conference Publication, 431:78–82, 1996Google Scholar
  6. 6.
    S. Batman and J. Goutsias. Unsupervised iterative detection of land mines in highly cluttered environments. IEEE Transactions on Image Processing, 12(5):509–523, 2003CrossRefGoogle Scholar
  7. 7.
    J.V. Beck, B. Blackwell, and S.R. St-Clair Jr. Inverse Heat Conduction. Ill-Posed Problems. Wiley, New York, 1995Google Scholar
  8. 8.
    C. Bruschini and B. Gros. A survey of current sensor technology research for the detection of land mines. In Sustainable Humanitarian Demining: Trends, Techniques and Technologies, pages 172–187, Mid Valley Press, Verona, VA, December 1998Google Scholar
  9. 9.
    H.S. Carslaw and J.C. Jaeger. Conduction of Heat in Solids, 2nd ed, Oxford University Press, Oxford, U.K., 1959Google Scholar
  10. 10.
    F. Cremer. Polarimetric infrared and sensor fusion for the detection of land mines. Ph.D. thesis, TNO Physics and Electronics Laboratory, The Hague, The Netherlands, 2003Google Scholar
  11. 11.
    F. Cremer, N.T. Thành, L. Yang, and H. Sahli. Stand-off thermal IR minefield survey, system concept and experimental results. In R.S. Harmon, J.T. Broach, and J.H. Holloway Jr., editors, Proceedings of SPIE 5794, Detection and Remediation Technologies for Mine and Minelike Targets X, pages 209–220, 2005Google Scholar
  12. 12.
    W. de Jong, H.A. Lensen, and Y.H.L. Janssen. Sophisticated test facility to detect land mines. In A.C. Dubey, James F. Harvey, J.T. Broach, and R.E. Dugan, editors, Proceedings of SPIE 3710, Detection and Remediation Technologies for Mine and Minelike Targets IV, pages 1409– 1418, Orlando, FL, Apr 1999Google Scholar
  13. 13.
    C.P. Gooneratne, S.C. Mukhopahyay, and G. Sen Gupta. A review of sensing technologies for land mine detection: unmanned vehicle based approach. In Second International Conference on Autonomous Robots and Agents, pages 401–407, Palmerston North, New Zealand, Dec 2004Google Scholar
  14. 14.
    D.N. Hào. Methods for Inverse Heat Conduction Problems. Peter Lang, Frankfurt am Main, Bern, New York, Paris, 1998Google Scholar
  15. 15.
    J. Hermann and I. Chant. Microwave enhancement of thermal land mine signatures. In A.C. Dubey and J.F. Harvey, editors, Proceedings of SPIE Vol. 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, pages 110–114, Orlando, FL, 1999Google Scholar
  16. 16.
    Q.A. Holmes, C.R. Schwartz, J.H. Seldin, J.A. Wright, and L.J. Witter. Adaptive multispectral CFAR detection of land mines. In Proceedings of SPIE, Vol. 2496, pages 421–432, 1995Google Scholar
  17. 17.
    V. Isakov. Inverse Problems for Partial Differential Equations, vol. 127 of Applied Mathematical Sciences, 2nd ed. Springer Science+Business Media, Inc. New York, 2006Google Scholar
  18. 18.
    P.A. Jacobs. Thermal Infrared Characterization of Ground Targets and Backgrounds. SPIE Optical Engineering Press, Bellingham, WA, 1996Google Scholar
  19. 19.
    Y.H.L. Janssen, A.N. de Jong, H. Winkel, and F.J.M. van Puten. Detection of surface laid and buried mines with IR and CCD cameras, an evaluation based on measurements. In A.C. Dubey, R.L. Barnard, C.J. Lowe, and J.E. McFee, editors, Proceedings of SPIE Vol. 2765, Detection and Remediation Technologies for Mines and Minelike Targets, pages 448–459, 1996Google Scholar
  20. 20.
    A.B. Kahle. A simple thermal model of the earth's surface for geologic mapping by remote sensing. Journal of Geophysical Research, 82:1673–1680, 1977CrossRefGoogle Scholar
  21. 21.
    K. Khanafer and K. Vafai. Thermal analysis of buried land mines over a diurnal cycle. IEEE Transactions on Geoscience and Remote Sensing, 40(2):461–473, 2002CrossRefGoogle Scholar
  22. 22.
    K. Khanafer, K. Vafai, and B.A. Baertlein. Effects of thin metal outer case and top air gap on thermal IR images of buried antitank and antipersonnel land mines. IEEE Transactions on Geoscience and Remote Sensing, 41(1):123–135, 2003CrossRefGoogle Scholar
  23. 23.
    L.A. Leschack and N.K. Del Grande. A dual-wavelength thermal infrared scanner as a potential arborne geophysical exploration tool. Geophysics, 41(6):1318–1336, 1976CrossRefGoogle Scholar
  24. 24.
    P. López. Detection of landmines from Measured Infrared images using thermal modelling of the soil. Ph.D. thesis, University of Santiago de Compostela, 2003Google Scholar
  25. 25.
    P. López, L. Van Kempen, H. Sahli, and D. C. Ferrer. Improved thermal analysis of buried land mines. IEEE Transactions on Geoscience and Remote Sensing, 4(9):1965–1975, 2004Google Scholar
  26. 26.
    G. Maksymomko, B. Ware, and D. Poole. A characterization of diurnal environmental effects on mines and the factors influencing the performance of mine detecting ATR algorithms. In A.C. Dubey, I. Cindrich, J.M. Ralston, and K.A. Rigano, editors, Proceedings of SPIE Vol. 2496, Detection and Remediation Technologies for Mines and Minelike Targets, pages 140– 151, 1995Google Scholar
  27. 27.
    A. Muscio and M.A. Corticelli. Experiments of thermographic land mine detection with reduced size and compressed time. Infrared Physics & Technology, 46(1–2):101–107, 2004CrossRefGoogle Scholar
  28. 28.
    A. Muscio and M.A. Corticelli. Land mine detection by infrared thermography: reduction of size and duration of the experiments. IEEE Transactions on Geoscience and Remote Sensing, 42(9):1955–1964, 2004CrossRefGoogle Scholar
  29. 29.
    J. Paik, C.P. Lee, and M.A. Abidi. Image processing-based mine detection techniques: a review. Subsurface Sensing Technologies and Applications, 3(3):153–202, 2002CrossRefGoogle Scholar
  30. 30.
    P. Pregowski, W. Swiderski, W.T. Walczak, and B. Usowicz. Role of time and space variability of moisture and density of sand for thermal detection of buried objects–modeling and experiments. In Dennis H. LeMieux and John R. Snell Jr., editors, Proceedings of SPIE 3700, Thermosense XXI, pages 444–455, 1999Google Scholar
  31. 31.
    K.L. Russel, J.E. McFee, and W. Sirovyak. Remote performance prediction for infrared imaging of buried mines. In A.C. Dubey and R.L. Barnard, editors, Proceedings of SPIE Vol. 3079, Detection and Remediation Technologies for Mines and Minelike Targets II, pages 762–769, 1997Google Scholar
  32. 32.
    H. Sahli, C. Bruschini, and S. Crabbe. Catalogue of Advanced Technologies and Systems for Humanitarian Demining. Eudem 2 technology survey report, v.1.3, Dept., of Electron Informatics, Vrije Universiteit Brussel, Brussels, Belgium, 2005.Google Scholar
  33. 33.
    A.A. Samarskii and P. N. Vabishchevich. Computational Heat Transfer. Volume 1: Mathematical Modelling. Wiley, Chichester, U.K., 1995Google Scholar
  34. 34.
    M. Schachne, L. Van Kempen, D. Milojevic, H. Sahli, P. van Ham, M. Acheroy, and J. Cornelis. Mine detection by means of dynamic thermography: simulation and experiments. In The Second International Conference on the Detection of Abandoned Landmines, pages 124–128, Edinburgh, U.K., October, 12–14, 1998Google Scholar
  35. 35.
    I.K. Sendur and B.A. Baertlein. Techniques for improving buried mine detection in thermal IR imagery. In A.C. Dubey, J.F. Harvey, J.T. Broach, and R.E. Dugan, editors, Proceedings of SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, pages 1272–1283, 1999Google Scholar
  36. 36.
    I.K. Sendur and B.A. Baertlein. Numerical simulation of thermal signatures of buried mines over a diurnal cycle. In A.C. Dubey, J.F. Harvey, J.T. Broach, and R.E. Dugan, editors, Proceedings of SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, pages 156–167, 2000Google Scholar
  37. 37.
    J.R. Simard. Improved land mine detection capability (ILDC): systematic approach to the detection of buried mines using passive IR imaging. In A.C. Dubey, R.L. Barnard, C.J. Lowe, and J.E. McFee, editors, Proceedings of SPIE Vol. 2765, Detection and Remediation Technologies for Mines and Minelike Targets, pages 489–500, 1996Google Scholar
  38. 38.
    S. Sjökvist. Heat transfer modelling and simulation in order to predict thermal signatures – the case of buried land mines. Ph.D. thesis, Linkopings University, Linkopings, Sweden, 1999Google Scholar
  39. 39.
    S. Sjökvist, R. Garcia-Padron, and D. Loyd. Heat transfer modelling of solar radiated soil, including moisture transfer. In Third Baltic Heat Transfer Conference, pages 707–714, Gdansk, Poland, September, 22–24, 1999, IFFM PublishersGoogle Scholar
  40. 40.
    S. Sjökvist, M. Georgson, S. Ringberg, M. Uppsall, and D. Loyd. Thermal effects on solar radiated sand surfaces containing land mines – a heat transfer analysis. In Fifth International Conference on Advanced Computational Methods in Heat Transfer, pages 177–187, Cracow, Poland, June, 17–19, 1998. Computational Mechanics PublicationsGoogle Scholar
  41. 41.
    S. Sjökvist, A. Linderhed, S. Nyberg, M. Uppsall, and D. Loyd. Land mine detection by IR temporal analysis: physical numerical modeling. In R.S. Harmon, J.T. Broach, and J.H. Holloway Jr., editors, Proceedings of SPIE 5794, Detection and Remediation Technologies for Mine and Minelike Targets X, pages 30–41, 2005Google Scholar
  42. 42.
    N.T. Thành. Infrared thermography for the detection and characterization of buried objects. Ph.D. thesis, Vrije Universiteit Brussel, Brussels, Belgium, 2007Google Scholar
  43. 43.
    N.T. Thành, D.N. Hào, P. López, F. Cremer, and H. Sahli. Thermal infrared identification of buried land mines. In R.S. Harmon, J.T. Broach, and J.H. Holloway Jr., editors, Proceedings of SPIE 5794, Detection and Remediation Technologies for Mine and Minelike Targets X, pages 198–208, 2005Google Scholar
  44. 44.
    N.T. Thành, D.N. Hào, and H. Sahli. Thermal model for land mine detection: efficient numerical methods and soil parameter estimation. In R.S. Harmon, J.T. Broach, and J.H. Holloway Jr., editors, Proceedings of SPIE 6217, Detection and Remediation Technologies for Mine and Minelike Targets XI, pages 517–528, 2006Google Scholar
  45. 45.
    N.T. Thành, H. Sahli, and D.N. Hào. Finite difference methods and validity of a thermal model for land mine detection with soil property estimation. IEEE Transactions on Geoscience and Remote Sensing, 45(3):656–674, 2007CrossRefGoogle Scholar
  46. 46.
    K. Watson. Geologic applications of thermal infared images. Proceedings of the IEEE, 63: 128–137, 1975CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Nguyen Trung Thành
    • 1
  • Dinh Nho Hào
    • 1
  • Hichem Sahli
    • 1
  1. 1.Vrije Universiteit BrusselDepartment of Electronics and InformaticsBrusselsBelgium

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