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‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐image data’ by M. Li, S. D. Holland and W. Q. Meeker: Discussion 2

‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐image... The paper written by M. Li, S. D. Holland and W. Q. Meeker (Applied Stochastic Models in Business and Industry) presents statistical methods for automatic Crack detection based on vibrothermography sequence‐of‐image data. In particular, a matched filter used to increase the signal‐to‐noise ratio is developed. The review gives suggestions about physical approach and detection criteria. Copyright © 2010 John Wiley & Sons, Ltd. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Stochastic Models in Business and Industry Wiley

‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐image data’ by M. Li, S. D. Holland and W. Q. Meeker: Discussion 2

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Publisher
Wiley
Copyright
Copyright © 2010 John Wiley & Sons, Ltd.
ISSN
1524-1904
eISSN
1526-4025
DOI
10.1002/asmb.865
Publisher site
See Article on Publisher Site

Abstract

The paper written by M. Li, S. D. Holland and W. Q. Meeker (Applied Stochastic Models in Business and Industry) presents statistical methods for automatic Crack detection based on vibrothermography sequence‐of‐image data. In particular, a matched filter used to increase the signal‐to‐noise ratio is developed. The review gives suggestions about physical approach and detection criteria. Copyright © 2010 John Wiley & Sons, Ltd.

Journal

Applied Stochastic Models in Business and IndustryWiley

Published: Sep 1, 2010

References