| 基于马尔可夫模型的JPEG图像隐写分析 |
| |
| 引用本文： | 童学锋,滕建忠,宣国荣,崔霞. 基于马尔可夫模型的JPEG图像隐写分析[J]. 计算机工程, 2008, 34(23): 217-219 |
| |
| 作者姓名： | 童学锋 滕建忠 宣国荣 崔霞 |
| |
| 作者单位： | 同济大学计算机科学与技术系,上海,200092 |
| |
| 基金项目： | 国家自然科学基金资助项目 |
| |
| 摘 要： | 论证了通用图像隐写分析是一个类间很聚合、类内很分散的2类模式识别的困难分类问题。提出一种基于JPEG图像量化DCT域的块内和块间2个马尔可夫链获得高维特征，给出2种高维特征的分类器，即改进贝叶斯分类器和CNPCA分类器，后者简单而性能略低，但仍略优于SVM分类器。针对4种公认的JPEG隐藏数据方法，即F5, Outguess, MB1和MB2进行隐写分析，在CorelDraw图像库上做实验，取得了较好的效果。
|
| 关 键 词： | 隐写分析 JPEG图像 DCT系数 马尔可夫模型 改进贝叶斯分类器 CNPCA分类器 |
| 修稿时间： | |
JPEG Image Steganalysis Based on Markov Model |
| |
| TONG Xue-feng,TENG Jian-zhong,XUAN Guo-rong,CUI Xia. JPEG Image Steganalysis Based on Markov Model[J]. Computer Engineering, 2008, 34(23): 217-219 |
| |
| Authors: | TONG Xue-feng TENG Jian-zhong XUAN Guo-rong CUI Xia |
| |
| Affiliation: | (Department of Computer Science, Tongji University, Shanghai 200092) |
| |
| Abstract: | This paper proves that the universal steganalysis is a difficult two-class recognition problem,of which the between-class distribution is quite close and the within-class distribution is very scattered.This paper proposes the high-dimension feature based on the two Markov models of inner-block and inter-blocks in DCT domain of JPEG image.The paper also proposes two types of classifiers for high-dimension classification.One is the improved Bayesian classifier,and the other is the Class-wise Non-Principal Com... |
| |
| Keywords: | steganalysis JPEG image DCT coefficient Markov model improved Bayesian classifier Class-wise Non-Principal Components Analysis(CNPCA) classifier |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载免费的PDF全文 |
