k均值聚类的混合异构图像隐写分析

doi:10.3969/j.issn.0255-8297.2014.05.017

Abstract

Abstract: 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.

Key words: information hiding, k-means clustering, image texture complexity, image steganalysis

CLC Number:

TP391

XIE Kai, ZHANG Tao, XI Ling, LI Wen-xiang, PING Xi-jian. Steganalysis of Heterogeneous Images Using k-Means Clustering[J]. Journal of Applied Sciences, 2014, 32(5): 543-550.

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Steganalysis of Heterogeneous Images Using k-Means Clustering

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