基于轮廓波变换的隐写分析算法

山东大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (2): 75-79.

基于轮廓波变换的隐写分析算法

师夏阳,王宇飞,胡永健

华南理工大学电子与信息学院, 广东广州 510641

收稿日期:2010-11-04 出版日期:2011-04-16 发布日期:2010-11-04
作者简介:师夏阳(1978- ), 男，河南平顶山人，博士研究生，主要研究方向为数字图像取证,隐写与隐写分析及图像处理. Email：eeyjhu@scut.edu.cn
基金资助:
国家自然科学基金资助项目（60772115，60572140)

A contourlet transform-based steganalysis algorithm

SHI Xiayang, WANG Yufei, HU Yongjian

School of Electronic and Information Engineering, South China University of Technology,
Guangzhou 510641, China

Received:2010-11-04 Online:2011-04-16 Published:2010-11-04

摘要/Abstract

摘要：

基于轮廓波变换对图像表示的优良性质,提出了一种基于轮廓波变换的通用隐写分析算法。综合了轮廓波变换高频子带系数、高频子带噪声残差、高频子带特征函数高阶统计模型,利用支持向量机(support vector machine,SVM)对JSteg、Jphide、F5、Outguess等隐写算法的不同嵌入率进行分类和检测。实验结果表明基于轮廓波变换隐写分析算法对大部分隐写算法具有优良的探测性能。与传统的小波变换相比,轮廓波变换能够更有效地捕捉到图像因密信的嵌入而引起的细微变化。

关键词: 隐写分析, 轮廓波变换, 统计特征

Abstract:

A universal steganalysis method was proposed by using the superior property of the contourlet transform with representation of an image. It merged the highorder statistics model of coefficient moments statistics, noise residual moments statistics, and characteristic function moments in the high frequency subband of the contourlet domain. At the same time, a nonlinear support vector machine(SVM) classifier was used to classify JSteg, Jphide, F5 and Outguess with different embedding rates. Experimental results showed that the proposed method has the superion discriminative performance for most of steganography methods. Compared with the classical wavelet, the contourlet transform has better detection effect to capture slight differences during embedding messages.

Key words: steganalysis, contourlet transform, statistics characteristic

师夏阳,王宇飞,胡永健. 基于轮廓波变换的隐写分析算法[J]. 山东大学学报(工学版), 2011, 41(2): 75-79.

SHI Xiayang, WANG Yufei, HU Yongjian. A contourlet transform-based steganalysis algorithm[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(2): 75-79.

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