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基于主成分分析的泛盲掩密分析方案

DOI: 10.11834/jig.20060364

Keywords: 掩密分析,泛盲掩密分析,主成分分析

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Abstract:

为了能够对掩密后图像进行有效的检测,首先从分类特征维数、单个特征的有效性和特征相关性等3个方面对Farid泛盲掩密分析算法的缺陷进行了分析,然后提出了采用主成分分析技术对分类特征进行降维处理的方法。并基于RBF(radialbasisfunction)网络构造了新的泛盲掩密分析方案。该方案不但大大降低了用于分类的图像特征的维数,而且提高了掩密分析的检测性能。利用该方案和Farid的方案分别对用JSteg等软件掩密后的图像进行的检测比较实验表明。经主成分分析预处理后。该方案的样本集特征矢量维数比Farid方案分别减少了174(Jsteg)维、163(EzStego)维和180(S-Tools)维,而特征数目的减少又大大简化了分类器的设计。而且。该方案能够有效检测嵌入消息占可嵌容量的比例达60%(Jsteg)、80%(EzStego)、50%(S-Tools)以上的掩密图像。并获得了比Farid算法更高的检测率。

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