Machine Vision and Applications

, Volume 20, Issue 6, pp 411–421 | Cite as

Computer vision system for high temperature measurements of surface properties

  • Anna FabijańskaEmail author
  • Dominik Sankowski
Original Paper


Recently, computer vision systems have become very popular. They are of great importance in almost every field of science, engineering and industry. Present-day vision systems allow to obtain information that is normally not distinguishable by humans. It is possible due to use of appropriate digital image processing and analysis algorithms. The paper explains importance of proper image processing algorithms selection for computer vision applications. Particular industrial image quantitative analysis systems are considered. Computerized system for high-temperature measurements of surface properties is used as an example. The system is capable of measuring wetting angle and surface tension of metals, alloys and other materials (e.g. glass) in temperatures up to 1,800°C. A brief description of the system is given. Particularly, attention is paid to preprocessing algorithms. They consider not only typical factors that usually accompany digital images founded analysis but also specificity of images obtained during the measurement process as well. Correction of factors arising from CCD camera electronic components and reduction of aura (glow that appears around specimen in high temperatures) affects with high quality image segmentation. In consequence the accuracy of surface parameters determination is increased.


Digital image processing Image quantitative analysis system High-temperature measurements Surface properties CCD camera Image enhancement 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adamson, A.W., Gast, A.P.: Physical Chemistry of Surface. Wiley-Interscience, USA (1997)Google Scholar
  2. 2.
    Atae-Allah, C., Cabrerizo-Vílchez, M., Gómez-Lopera, J.F. et al.: Measurement of surface tension and contact angle using entropic edge detection. Meas. Sci. Technol. 12, 288–298 (2001)CrossRefGoogle Scholar
  3. 3.
    Emel’yanenko, A.M., Boinovich, L.B.: The use of digital processing of video images for determining parameters of sessile and pendant drops. Colloid J. 63(2), 159–172 (2001)CrossRefGoogle Scholar
  4. 4.
    Hansen, F.K.: Surface tension by image analysis: fast and automatic measurements of pendant and sessile drops and bubbles. J. Colloid Interface Sci. 160, 209–217 (1993)CrossRefGoogle Scholar
  5. 5.
    Cabrerizo-Vílchez, M.A., Wege, H.A., Holgado-Terriza, J.A.: Axisymmetric drop shape analysis as penetration Langmuir balance. Rev. Sci. Instrum. 70(5), 2438–2443 (1999)CrossRefGoogle Scholar
  6. 6.
    del Río, O.I., Neumann, A.W.: Axisymmetric drop shape analysis: computational methods for the measurement of interfacial properties from the shape and dimensions of pendant and sessile drops. J. Colloid Interface Sci. 196, 136–147 (1997)CrossRefGoogle Scholar
  7. 7.
    Wulf, M., Michel, S., Grundke, K. et al.: Simultaneous determination of surface tension and density of polymer melts using axisymmetric drop shape analysis. J. Colloid Interface Sci. 210, 172–181 (1999)CrossRefGoogle Scholar
  8. 8.
    Cabezasa, M.G., Batenib, A., Montanero, J.M., Neumannb, A.W.: A new drop-shape methodology for surface tension measurement. Appl. Sur. Sci. 38(14), 480–484 (2004)CrossRefGoogle Scholar
  9. 9.
    DeGennes, P., Brochard-Wyart, F., Quere, D.: Capillarity and Wetting Phenomena: Drops, Bubbles, Pearls, Waves. Springer, Germany (2003)Google Scholar
  10. 10.
    Hartland, S. (eds): Surface and Interfacial Tension: Measurement, Theory, and Applications. CRC, USA (2004)Google Scholar
  11. 11.
    DeGennes, P.G.: Wetting: statics and dynamics. Rev. Mod. Phys. 57, 827–863 (1985)CrossRefGoogle Scholar
  12. 12.
    Bachevsky, R.S., Naidich, Y.V., Grygorenko, M.F., Dostojny, V.A.: Evaluation of errors in automatic image analysis determination of sessile drop shapes. In: Proceedings of International Conference on High Temperature Capillarity, Smolenice Castle, Poland, pp. 254–258 (1994)Google Scholar
  13. 13.
    Huh, C., Reed, R.L.: A method for estimating interfacial tensions and contact angles from sessile and pendant drop shapes. J. Colloid and Interface Science 9, 1472–1484 (1983)Google Scholar
  14. 14.
    Hansen, F.K.: Surface tension by image analysis: fast and automatic measurements of pendant and sessile drops and bubbles. J. Colloid Interface Sci. 160, 209–217 (1993)CrossRefGoogle Scholar
  15. 15.
    Matveev V.M., Kheifets K.O., Philippov V.V., Popel P.S.: Automatic measurement of surface tension and density in melts by the sessile drop method. In: Proceedings of International Conference on High Temperature Capillarity, Smolenice Castle, pp. 259–263 (1994)Google Scholar
  16. 16.
    Bachevsky R.S., Naidich Y.V., Grygorenko M.F., Dostojny V.A.: Evaluation of Errors in automatic Image Analysis Determination of Sessile Drop Shapes. In: Proceedings of International Conference on High temperature Capillarity, Smolenice Castle, pp. 254–258 (1994)Google Scholar
  17. 17.
    G10 Contact Angle Measuring Instrument. Mat. Krüss GmbH, Hamburg (1995)Google Scholar
  18. 18.
  19. 19.
    VCA 2000 Video Contact Angle Meter. Mat. Kernco Instruments Co. Inc., El Paso (1999)Google Scholar
  20. 20.
    Woodward R.P.: Two-Dimensional Contact Angle and Surface Tension Mapping. Ed. First Ten Angstroms, Portsmouth (1996)Google Scholar
  21. 21.
  22. 22.
  23. 23.
  24. 24.
    Gunter, I.A, Jacobson, D.M.: The GEC meniscograph solderability tester: adaptation to vacuum soldering. GEC Rev. 6(2), 86–89 (1990)Google Scholar
  25. 25.
    Vincent, J.H., Humpston, G.: Lead-free solders for electronics assembly. GEC J Res. 11, 76–89 (1994)Google Scholar
  26. 26.
  27. 27.
    Sankowski, D., Strzecha, K., Jezewski, S.: Digital image analysis in measurement of surface tension and wettability angle. In: Proceedings of International Conference on Modern Problems of Telecommunications, Computer Science and Engineers Training, Lviv-Slavskie, Ukraine, 129–130 (2000)Google Scholar
  28. 28.
    Sankowski, D., Senkara, J., Strzecha, K., Jezewski, S.: Automatic investigation of surface phenomena in high temperature solid and liquid contacts. In: Proceedings of IEEE Instrumentation and Measurement Technology Conference IMTC, Budapest, Hungary, 1397–1400 (2001)Google Scholar
  29. 29.
    Sankowski, D., Senkara, J., Strzecha, K.: Computerized system for assessment of quality of solders. In: Proceedings of International Conference on IEEE The Experience of Designing and Application of CAD Systems in Microelectronics, CADSM, Lviv-Slavske, Ukraine, 56–58 (2003)Google Scholar
  30. 30.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, USA (2002)Google Scholar
  31. 31.
    Pratt, W.K.: Digital Image Processing. Wiley, USA (2001)CrossRefGoogle Scholar
  32. 32.
    Jahne, B.: Digital Image Processing. Springer, Germany (2002)Google Scholar
  33. 33.
    Young, I.T., Gerbrands, J.J., van Vliet, L.J.: Fundamentals of Image Processing. Delft University of Technology, The Netherlands (1998)Google Scholar
  34. 34.
    Howell, S.B.: Handbook of CCD Astronomy. Cambridge University Press, UK (2006)Google Scholar
  35. 35.
    Martinez, P., Klotz, A.: A Practical Guide to CCD Astronomy. Cambridge University Press, UK (1998)Google Scholar
  36. 36.
    Fabijanska, A., Sankowski, D.: Aura removal algorithm for high-temperature image quantitative analysis systems. In: Proceedings Internation Conference of Mixed Design of Integrated Circuits and Systems, MIXDES, Ciechocinek, Poland, pp. 617–621 (2007)Google Scholar
  37. 37.
    Halliday, D., Resnick, R., Walker, J.: Fundamentals of Physics. Wiley, USA (2004)Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Computer Engineering DepartmentTechnical University of LodzLodzPoland

Personalised recommendations