PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Advantages of Using Feature Selection Techniques on Steganalysis Schemes
Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten and Olli Simula
In: 9th InternationalWork-Conference on Artificial Neural Networks LNCS , 4507/2007 . (2007) Springer-Verlag , Berlin Heidelberg , pp. 606-613. ISBN 978-3-540-73006-4

Abstract

Steganalysis consists in classifying documents as steganographied or genuine. This paper presents a methodology for steganalysis based on a set of 193 features with two main goals: determine a sufficient number of images for effective training of a classifier in the obtained high-dimensional space, and use feature selection to select most relevant features for the desired classification. Dimensionality reduction is performed using a forward selection and reduces the original 193 features set by a factor of 13, with overall same performance.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:3733
Deposited By:Amaury Lendasse
Deposited On:15 February 2008