Blind image steganalysis based on run-length histogram analysis

Abstract

In this paper, a new, simple but effective method is proposed for blind image steganalysis, which is based on run-length histogram analysis. Higher-order statistics of characteristic functions of three types of image run-length histograms are selected as features. Support vector machine is used as classifier. Experimental results demonstrate that the proposed scheme significantly outperforms prior arts in detection accuracy and generality. © 2008 IEEE.

Publication
Proceedings - International Conference on Image Processing, ICIP
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Jing Dong
Associate Prof., Master Tutor

Mainly engaged in the research work of multimedia content security, artificial intelligence security, multimodal content analysis and understanding.

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