Journal of the Korean Society for Nondestructive Testing (비파괴검사학회지)

The Korean Society for Nondestructive Testing (한국비파괴검사학회)
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Development of Calibration Target for Infrared Thermal Imaging Camera

적외선 열화상 카메라용 캘리브레이션 타겟 개발

  • 김수언 (한국표준과학연구원 삶의질측정표준본부) ;
  • 최만용 (한국표준과학연구원 삶의질측정표준본부) ;
  • 박정학 (한국표준과학연구원 삶의질측정표준본부) ;
  • 신광용 (상명대학교 문화기술연구소) ;
  • 이의철 (상명대학교 컴퓨터과학과)
  • Received : 2014.05.13
  • Accepted : 2014.06.21
  • Published : 2014.06.30
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Abstract

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration cannot be applied to the calibration of mid-wave and long-wave infrared cameras. Recently, with the growing use of infrared thermal cameras that can measure defects from thermal properties, development of an applicable calibration target has become necessary. Thus, based on heat conduction analysis using finite element analysis, we developed a calibration target that can be used with both existing visible cameras and infrared thermal cameras, by implementing optimal design conditions, with consideration of factors such as thermal conductivity and emissivity, colors and materials. We performed comparative experiments on calibration target images from infrared thermal cameras and visible cameras. The results demonstrated the effectiveness of the proposed calibration target.

카메라 영상 캘리브레이션은 머신비전과 같은 비전검사기술분야에서 영상으로부터 기하학적 정보를 정확하게 추출하고자 할 때 정확성을 높이는데 필요한 매우 중요한 과정이다. 그러나 기존에 가시광 카메라에 사용되던 캘리브레이션 타겟은 중적외선, 원적외선 열화상 카메라에 적용하기 어렵다. 최근에 적외선 열화상카메라를 이용한 결함측정기술이 많이 사용되면서 적용할 수 있는 캘리브레이션 타겟 개발이 요구되고 있다. 따라서 본고에서는 유한요소 열전달 해석을 이용하여 가시광 카메라와 적외선 열화상카메라 모두에 적용 가능한 캘리브레이션 타겟을 제안하였다. 개발된 캘리브레이션 타겟을 열화상카메라와 가시광 카메라로 촬영하여 비교실험 하였으며, 실험결과 제안된 캘리브레이션 타겟의 효율성을 보여준다.

Keywords

References

  1. L. N. Smith and M. L. Smith, "Automatic machine vision calibration using statistical and neural network methods," Image and Vision Computing, Vol. 23, No. 10, pp. 887-899 (2005) https://doi.org/10.1016/j.imavis.2005.03.009
  2. I. J. Aldave, P. V. Bosom, L. V. Gonzalez, I. L. de Santiago, B. Vollheim, L. Krausz and M. Georges, "Review of thermal imaging systems in composite defect detection," Infrared Physics and Technology, Vol. 61, pp. 167-175 (2013) https://doi.org/10.1016/j.infrared.2013.07.009
  3. Z. Zhang, "A flexible new technique for camera calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 11, pp. 1330-1334 (2000) https://doi.org/10.1109/34.888718
  4. S. Y. Cheng, S. Park and M. M. Trivedi, "Multiperspective thermal IR and video arrays for 3D body tracking and driver activity analysis," In CVPR'05 proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 3-3 (2005)
  5. P. Bajcsy and S. Saha, "A new thermal infrared camera calibration approach using wireless MEMS sensors," Proceeding of the Communication Networks and Distributed Systems Modeling And Simulation Conference, pp. 1-6 (2004)
  6. R. Yang, W. Yang, Y. Chen and X. Wu, "Geometric calibration of IR camera using trinocular vision," Journal of Lightwave Technology, Vol. 29, pp. 3797-3803 (2011) https://doi.org/10.1109/JLT.2011.2170812
  7. T. Luhmann, J. Ohm, J. Piechel and T. Roelfs, "Geometric calibration of thermographic cameras," Proceedings of International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Part 5 Commission V Symposium, Newcastle upon Tyne, UK. XXXVIII 411-415 (2010)
  8. W. Ursine, F. Calado, G. Teixeira, H. Diniz, S. Silvino and R. de Andrade, "Thermal/ Visible Autonomous Stereo Visio System Calibration Methodology for Non-controlled Environments," Proceedings of 11th International Conference on Quantitative Infrared Thermography, Naples Italy (2012)
  9. C. C. Slama, C. Theurer and S. W. Henriksen, "Manual of Photogrammetry," 4th ed.; American Society of Photogrammetry: Falls Church, VA, USA (1980)
  10. R. Lenz and D. Fritsch, "Accuracy of videometry with CCD sensors," ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 45, No. 2, pp. 90-110 (1990) https://doi.org/10.1016/0924-2716(90)90095-S
  11. S. Lanser, C. Zierl, and R. Beutlhauser, "Multibildkalibrierung einer CCD-Kamera," Mustererkennung, Informatik aktuell, G. Sagerer, S. Posch, F. Kummert, Eds.; Springer-Verlag: Berlin, Germany, pp. 481-491 (1995)
  12. B. Prescott and G. F. McLean, "Line-Based Correction of Radial Lens Distortion," Graphical Models and Image Processing, Vol. 59, pp. 39-47 (1997) https://doi.org/10.1006/gmip.1996.0407
  13. J. Heikkila, "Geometric camera calibration using circular control points," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, pp. 1066-1077 (2000) https://doi.org/10.1109/34.879788
  14. C. Steger, M. Ulrich and C. Wiedemann, "Machine Vision Algorithms and Applications," WILEY-VCH Verlag Gmbh & Co. KGaA., pp. 180-198 (2008)

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