Reduce Measurement Uncertainty of Ball Crater Method by Using Image Processing Techniques

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 110)


A method of reducing the uncertainty in measuring coating thickness using the ball crater method is proposed in this research. A crucial step of the ball crater method is measurement of the radii of the crater circles from a microscope image. While traditional methods of measuring the radii involve human operators, who inevitably introduce measurement uncertainty, the proposed approach measures a radius by fitting a circle (or an ellipse) to all edge points of a crater circle edge, which is extracted from the microscope image of the crater by using image processing techniques. This eliminates the subjectiveness introduced by human operators and reduces the measurement uncertainty. Experimental results confirm the feasibility of our method and its potential in reducing measurement uncertainty and increasing measurement accuracy of the ball crater method. The use of all edge points in the estimation of the radius in the proposed method also enables accurate determination of coating thickness from an image of a crater taken from a direction other than the normal to the coating surface.


Digital image processing Measurement uncertainty Thickness measurement Coatings 



The authors would like to acknowledge the financial support of TSB/Advantage W. Midlands under KTP Partnership No. 006504.


  1. 1.
    Gee MG, Gant A, Hutchings I, Bethke R, Schiffman K, Van Acker K, Poulat S, Gachon Y, von Stebut J (2003) Progress towards standardisation of ball cratering. Wear 255:1–13CrossRefGoogle Scholar
  2. 2.
    Teer BC-2 (2009) Ball crater device specification and user guide. Teer Coatings Ltd, DroitwichGoogle Scholar
  3. 3.
    Huang JG, Liatsis P, Cooke K (2011) Improving measurement repeatability of ball crater method by using image processing techniques, lecture notes in engineering and computer science: proceedings of the international multiconference of engineers and computer scientists 2011, IMECS 2011, Hong Kong, 16–18 March 2011Google Scholar
  4. 4.
    Relf CG (2004) Image acquisition and processing with LabVIEW. CRC, Boca RatonGoogle Scholar
  5. 5.
    Levenberg K (1944) A method for the solution of certain non-linear problems in least squares. Quart Appl Math 2:164–168MATHMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.School of Engineering and Mathematical SciencesCity University LondonLondonUK
  2. 2.Teer Coatings Ltd., Berry Hill Industrial EstateWorcestershireUK

Personalised recommendations