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Reversible data hiding in binary images based on image magnification

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Abstract

Over the past few years, many methods have been proposed for reversible data hiding in digital images, but few have been applied to binary images. The existing methods mainly employ run-length to embed the secret message, but the capacity is low. In this paper, we propose a reversible data hiding method based on image magnification. Firstly, image cross-shape patterns are analyzed to select the reference block pattern. Then, to improve the capacity and ensure reversibility, an image magnification strategy based on the reference block pattern is designed to scale up the original image to get the reference image. Finally, to ensure the visual quality of stego image, an inner-block flippable pixel selection strategy is designed to embed data. Experimental results have demonstrated that the proposed reversible data hiding scheme can restore the original image after extracting the embedded message, and achieve high embedding capacity and good visual quality.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (No. U1736118), the Natural Science Foundation of Guangdong (No. 2016A030313350), the Special Funds for Science and Technology Development of Guangdong (No. 2016KZ010103), the Key Project of Scientific Research Plan of Guangzhou (No. 201804020068), Shanghai Minsheng Science and Technology Support Program (17DZ1205500), Shanghai Sailing Program (17YF1420000), the Fundamental Research Funds for the Central Universities (No. 16lgjc83 and No. 17lgjc45).

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  1. School of Data and Computer Science, Guangdong Key Laboratory of Information Security Technology, Key Laboratory of Machine Intelligence and Advanced Computing (Ministry of Education), Sun Yat-sen University, Guangzhou, 510006, China

    Fang Zhang, Wei Lu, Hongmei Liu, Yuileong Yeung & Yingjie Xue

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  1. Fang Zhang
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  2. Wei Lu
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Zhang, F., Lu, W., Liu, H. et al. Reversible data hiding in binary images based on image magnification. Multimed Tools Appl 78, 21891–21915 (2019). https://doi.org/10.1007/s11042-019-7519-2

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