Efficient Parallel Feature Selection for Steganography Problems
Abstract
The Steganography Problem Consists of the Identification of Images Hiding a Secret Message, Which Cannot Be Seen by Visual Inspection. This Problem is Nowadays Becoming More and More Important Since the World Wide Web Contains a Large Amount of Images, Which May Be Carrying a Secret Message. Therefore, the Task is to Design a Classifier, Which is Able to Separate the Genuine Images from the Non-Genuine Ones. However, the Main Obstacle is that There is a Large Number of Variables Extracted from Each Image and the High Dimensionality Makes the Feature Selection Mandatory in Order to Design an Accurate Classifier. This Paper Presents a New Efficient Parallel Feature Selection Algorithm based on the Forward-Backward Selection Algorithm. the Results Will Show How the Parallel Implementation Allows to Obtain Better Subsets of Features that Allow the Classifiers to Be More Accurate. © 2009 Springer Berlin Heidelberg.
Recommended Citation
A. Guillén et al., "Efficient Parallel Feature Selection for Steganography Problems," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5517 LNCS, no. PART 1, pp. 1224 - 1231, Springer, Aug 2009.
The definitive version is available at https://doi.org/10.1007/978-3-642-02478-8_153
Department(s)
Engineering Management and Systems Engineering
International Standard Book Number (ISBN)
978-364202477-1
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
20 Aug 2009
