10 April 2018 Steganalysis based on reducing the differences of image statistical characteristics
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106151J (2018) https://doi.org/10.1117/12.2304572
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
Abstract
Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.
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Ran Wang, Ran Wang, Shaozhang Niu, Shaozhang Niu, Xijian Ping, Xijian Ping, Tao Zhang, Tao Zhang, } "Steganalysis based on reducing the differences of image statistical characteristics", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106151J (10 April 2018); doi: 10.1117/12.2304572; https://doi.org/10.1117/12.2304572
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