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Low-cost thermal scanner image enhancement by merging thermal and visual data

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EN
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EN
This paper demonstrates the application of different image processing techniques to process high resolution visual images and merge it with low resolution thermograms to improve its level of detail. The same idea is applied in commercially available thermal cameras (e.g. FLIR with MSX® technology). Low resolution thermograms considered in this paper were obtained from a thermal scanner with point infrared detector (Fig. 1) sensitive to long wavelength infrared spectral range. The proposed algorithms are Laplacian, Sobel operator, embossing and Gaussian differential blur (described in section 3). The authors processed 6 different thermograms to qualitatively assess obtained results. It was done in a statistical manner through a survey and revealed that both Sobel operator and embossing provided the most clear, detailed and unambiguous results (Fig. 5). Such algorithms may be applied for processing more channels in a multispectral, cost-effective system.
Wydawca
Rocznik
Strony
184--186
Opis fizyczny
Bibliogr. 11 poz., fot., rys., wykr., wzory
Twórcy
autor
  • Lodz University of Technology, Inst. of Electronics, 90-924 Łódź, Wólczańska 211/215 St.
  • Lodz University of Technology, Inst. of Electronics, 90-924 Łódź, Wólczańska 211/215 St.
Bibliografia
  • [1] FLIR Systems, Multi Spectral Dynamic Imaging (MSX®) Brochure.
  • [2] Więcek B, Zwolenik S.: Multichannel thermography system for real-time and transient thermal process application. Proc. Of Eurotherm Seminar n° 60, QIRT 4, Łódź, pp. 322-326, 1998.
  • [3] Melexis. MLX90614 family Single and Dual Zone Infrared Thermometer in TO-39. Datasheet, 2015. Available online: http://www.melexis.com/Asset/IR-sensor-thermometer-MLX90614-Datasheet-DownloadLink-5152.aspx
  • [4] Burger W, Burge M.: Principles of digital image processing: core algorithms. Springer, pp. 231–232, 2009.
  • [5] Militowski S.: Skaner termograficzny z możliwością nakładania przetworzonych obrazów rejestrowanych w wybranych zakresach widmowych. M.Sc. Thesis, Lodz University of Technology, 2015.
  • [6] Haralick R, Shapiro L.: Computer and Robot Vision, Vol. 1. Addison-Wesley Publishing Company, pp. 346 – 351, 1992.
  • [7] Vernon D.: Machine Vision. Prentice-Hall, pp. 92-99, 1991.
  • [8] Boyle R, Thomas R.: Computer Vision: A First Course. Blackwell Scientific Publications, pp. 48–50, 1988.
  • [9] Max N., Becker B.: Bump Shading for Volume Textures. IEEE Computer Graphics and Animation, pp. 18-20, 1994.
  • [10] Huang Z., Zhang X., Zhang W., Hou L.: A New Embossing Method for Gray Images Using Kalman Filter. Applied Mechanics and Materials, Vol. 39, pp. 488-491, 2010.
  • [11] Young R.: The Gaussian derivative model for spatial vision: I. Retinal mechanisms, Spatial Vision, Volume 2, Issue 4, pp. 273–293, 1987.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e6c5df8a-2ec4-46e4-8d1f-48decffb0298
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