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Proceedings Paper

Bayesian approach to attack characterization using robust watermarks
Author(s): Henry D Knowles; Dominique A. Winne; C. Nishan Canagarajah; David R. Bull
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Paper Abstract

In this paper we propose the use of a Bayesian framework to allow characterisation of image tampering from a library of attacks. We use the double watermarking strategy proposed in our previous work to derive sufficient information to drive the classifier. A non-parametric Bayesian classifier, trained on data derived from Monte Carlo simulations is used. In addition to classification, the effects of varying the input parameters are studied. The results obtained show that the non-parametric Bayesian classifier has a very low misclassification rate for this type of problem. Explanations as to the nature of the results, and some of the practical considerations, are given.

Paper Details

Date Published: 23 June 2003
PDF: 11 pages
Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); doi: 10.1117/12.503067
Show Author Affiliations
Henry D Knowles, Univ. of Bristol (United Kingdom)
Dominique A. Winne, Univ. of Bristol (United Kingdom)
C. Nishan Canagarajah, Univ. of Bristol (United Kingdom)
David R. Bull, Univ. of Bristol (United Kingdom)

Published in SPIE Proceedings Vol. 5150:
Visual Communications and Image Processing 2003
Touradj Ebrahimi; Thomas Sikora, Editor(s)

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