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An Evaluation of an Automated Detection Algorithm to Count Defects Present in X-Ray Topographical Images of SiC Wafers

Published online by Cambridge University Press:  01 February 2011

Ian Brazil
Affiliation:
ibrazil@runbox.com, RINCE, Dublin City University, Dublin 9,, Ireland, Dublin, N/A, Ireland
Patrick J. McNally
Affiliation:
mcnallyp@eeng.dcu.ie, Dublin City University, RINCE, Dublin, 9, Ireland
Lisa O'Reilly
Affiliation:
oreillyl@eeng.dcu.ie, Dublin City University, RINCE, Dublin, 9, Ireland
Andreas Danilewsky
Affiliation:
a.danilewsky@krist.uni-freiburg.de, Universität Freiburg, Kristallographisches Institute, Freiburg, N/A, Germany
Turkka O. Tuomi
Affiliation:
turkka.o.tuomi@hut.fi, Helsinki University of Technology, Helsinki, N/A, Finland
Aapo Lankinen
Affiliation:
aapo.lankinen@hut.fi, Helsinki University of Technology, Helsinki, N/A, Finland
Antti Säynätjoki
Affiliation:
antti.saynatjoki@hut.fi, Helsinki University of Technology, Helsinki, N/A, Finland
Rolf Simon
Affiliation:
Rolf.Simon@iss.fzk.de, Institut für Synchrotronstrahlung (ISS), Karlsruhe, N/A, Germany
Stanislav Soloviev
Affiliation:
soloviev@research.ge.com, GE Global Research, Niskayuna, NY, 12309, United States
Larry B. Rowland
Affiliation:
rowland@crd.ge.com, GE Global Research, Niskayuna, NY, 12309, United States
Peter M. Sandvik
Affiliation:
sandvik@crd.ge.com, GE Global Research, Niskayuna, NY, 12309, United States
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Abstract

An evaluation of an algorithm used to extract Threading Screw Dislocation defect data from Synchrotron White Beam X-Ray Topographical images of SiC wafers is reported. This extraction involves a two-fold process; firstly the algorithm highlights the appropriate defect and secondly updates the counter to provide a final result of defect count. The result of the automated algorithm is compared to hand counts in all cases, this allowing a critical analysis of the technique. Improvements to this algorithm have been made since last reported by the same authors, which are discussed. The analysis herein was also performed on a much larger sample of SiC wafer images than previously used by the same authors [1] allowing a better judgment of performance and critical evaluation. The algorithm is also compared with a previous algorithm that was used. Advantages and deficiencies in the algorithm are outlined and other potential avenues for extraction of the data are also discussed.

Type
Research Article
Copyright
Copyright © Materials Research Society 2007

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References

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