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Mixed Norm Regularized Discrimination for Image Steganalysis

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Abstract

The purpose of image steganalysis is to detect the presence of hidden messages in cover images. Steganalysis can be considered as a pattern recognition process to decide which class a test image belongs to: the innocent photographic image or the stego-image. This paper presents a definition of mixed \(L_{p,q}\) matrix norm as an extension of \(L_{2,1}\) matrix norm. We incorporate discriminative mixed \(L_{p,q}\) matrix norm analysis to select the features which best preserve the data distribution, e.g., manifold structure, of the whole feature sets. Experiments on different data sets verify the effectiveness of the proposed approach and the selected features are more discriminate.

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Acknowledgments

This work is partially supported by National Natural Science Foundation of China (Nos. 61370186, 61100170), Appropriative Researching Fund for Professors and Doctors, Guangdong University of Education (2013ARF03), Provincial research personnel fostered by Guangdong Province in the Thousand, Hundred and Ten Project, Guangdong Modern Information Service Industry Develop Particularly item (No. GDEID2011IS064), Fundamental Research Funds for the Central Universities (No. 12lgpy37), Ministry of education and China Mobile Research Fund (No. MCM20121051), Science and Technology Application Foundation Program of Guangzhou (No. 2014J4100032).

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Authors and Affiliations

  1. Department of Computer Science, Guangdong University of Education, Guangzhou, 510310, Guangdong, China

    Guoming Chen & Qiang Chen

  2. Sun Yat-sen University, Guangzhou, 510275, Guangdong, China

    Dong Zhang

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  1. Guoming Chen
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  2. Qiang Chen
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  3. Dong Zhang
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Correspondence to Guoming Chen.

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Chen, G., Chen, Q. & Zhang, D. Mixed Norm Regularized Discrimination for Image Steganalysis. Sens Imaging 16, 17 (2015). https://doi.org/10.1007/s11220-015-0120-5

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  • DOI: https://doi.org/10.1007/s11220-015-0120-5

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