摘要
基于小波系数相关性,提出了一类具有较高正确检测率的空域隐写通用型检测方法。首先利用互信息分析秘密信息嵌入对图像小波系数在尺度方向和空间方向相关性的影响,并使用马尔可夫模型挖掘小波系数层内和层间相关性,提取转移概率矩阵作为特征;然后对提取的特征进行加权融合并结合Fisher线性判别(FLD)分类器进行分类。针对LSB(least significant bit)、LSBmatching和SM(stochastic modulation)隐写算法的实验表明,在不增加计算复杂度的情况下,本文方法相比现有的典型空域隐写通用型检测方法,正确检测率有明显提高。
Based on wavelet coefficient dependency,a novel general image steganalysis technique for spatial domain steganography is proposed.First,the mutual information is exploited to analyze the change on the scale and orientation dependency between wavelet coefficients,which is caused by the embedding of a message,and the Markov model is applied to model the dependency between wavelet cofficients so as to extract intrascale and interscale transition probability matrices which are used as feature vectors.Then,a weighted feature fusion method is used to fuse these feature vectors and the fisher linear discriminant（FLD） is designed to classify them.The experiments on least significant bit（LSB）,LSB matching and stochastic modulation（SM） steganography show that the method can detect stego images reliably and the detection accuracy of this method exceeds that of its closest competitors obviously under the same computer complexity.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2012年第5期972-979,共8页
Journal of Optoelectronics·Laser
基金
国家自然科学基金(61103230
61103231)资助项目
关键词
隐写
隐写分析
小波系数
相关性
steganography
steganalysis
wavelet coefficient
dependency
