k均值聚类的混合异构图像隐写分析

提出了一种基于k均值聚类的混合异构图像隐写分析算法. 在训练阶段，根据图像纹理复杂度对图像库
进行聚类，并针对每一类图像训练相应的分类器. 在测试阶段，根据测试图像的纹理复杂度对其进行类别判断，然
后送至相应类别的分类器中进行隐写检测，从而减弱了失配状态对现有隐写分析算法造成的影响. 实验结果表明，
该算法较好地提高了现有隐写分析算法的检测精度.

Steganalysis of Heterogeneous Images Using k-Means Clustering

A new image steganalysis method using k-means clustering is presented. In the training phase,
the input images are classified to several classes using k-means clustering according to texture complexity.
The training process is specialized for each class separately. In the testing phase, the given test image is first
classified to the class it belongs to according to its texture complexity. It is then submitted to the corresponding
steganalysis classifier. The proposed method can reduce mismatch penalty considerably. Experimental results
demonstrate that the method can significantly enhance detection accuracy of existing steganalysis methods.