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Feature selection for image steganalysis using hybrid genetic algorithm

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成果类型:
期刊论文
作者:
Xia, Zhihua;Sun, Xingming;Qin, Jiaohua;Niu, Changming
通讯作者:
Sun, X.
作者机构:
[Niu, Changming; Qin, Jiaohua; Sun, Xingming; Xia, Zhihua] School of Computer and Communication, Hunan University, Changsha, 410082, China
[Sun, Xingming] YueluMountain, Changsha, Hunan, 410082, China
[Qin, Jiaohua] Department of Mathematics and Computer, Hunan City University, Yiyang, 413000, China
通讯机构:
[Sun, X.] Y
YueluMountain, Changsha, Hunan, 410082, China
语种:
英文
关键词:
Feature selection;Information security;Local convergence;Similarity among individuals;Transformation of generations
期刊:
Information Technology Journal
ISSN:
1812-5638
年:
2009
卷:
8
期:
6
页码:
811-820
机构署名:
本校为其他机构
院系归属:
理学院
摘要:
Learning-based methodology has been demonstrated to be an effective approach to dispose the steganalysis difficulties due to the variety of image texture. A crucial process of the learning-based steganalysis is to construct a low-dimensional feature set. In this study, a feature selection method based on Hybrid Genetic Algorithm (HGA) is presented to select feature subsets which not only contain fewer features, but also provide better detection performance for steganalysis. First, the general framework about utilizing Genetic Algorithm (GA) to ...

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