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Steganalysis of JPEG images by block texture based segmentation

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Abstract

The current JPEG steganalysis systems have attained outstanding achievements. A considerable variety of strategies for feature extraction are developed. However, a common shortcoming in the traditional image steganalysis techniques is that they are conducted on the entire image and do not take advantage of the content diversity. In this paper, a new steganalysis algorithm based on image segmentation is proposed to enable us to utilize the content characteristics of JPEG images. The images are segmented into several sub-images according to the texture complexity. The steganalysis features of each type of sub-images with the same or close texture complexity are extracted separately to build a classifier. The steganalysis results of the entire image are determined through a weighted fusing process. Experimental results demonstrate that the proposed method exhibits excellent performance and significantly improves the detection accuracy.

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Authors and Affiliations

  1. Zhengzhou Information Science and Technology Institute, Zhengzhou, Henan, 450002, China

    Ran Wang, Mankun Xu, Xijian Ping & Tao Zhang

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  1. Ran Wang
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  2. Mankun Xu
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  3. Xijian Ping
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  4. Tao Zhang
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Correspondence to Ran Wang.

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Wang, R., Xu, M., Ping, X. et al. Steganalysis of JPEG images by block texture based segmentation. Multimed Tools Appl 74, 5725–5746 (2015). https://doi.org/10.1007/s11042-014-1880-y

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