Abstract
Unauthorized Internet attacks against the watermarked images lead to the impossibility of a blind watermark extraction if the transmitted image is not normalized to its original geometric state. The aim of this study is to detect the regions in the watermarked image robust to rotation, scaling and translation (RST) attacks, enforced by additional immunity to JPEG lossy compression. Our algorithm is based on the simulation of JPEG lossy compression with following extraction of feature points using handcrafted and deep learning approaches. We incorporate JSNet as a JPEG simulator and Key.Net as an enforced way to find feature points invariant to RST attacks. As a result, we select the best anchor points, the coordinates of which are put into the secret key. Applying the same procedure to the transmitted image, we detect and recalculate the positions of the anchor points in the transmitted watermarked image, geometrically synchronizing with the original watermarked image and successfully extract the watermark. To address the mobile aspect, we exploited the simplest deep network architectures as far as the problem allowed with other clarifications.
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Acknowledgements
The reported study was funded by the Russian Fund for Basic Researches according to the research project no. 19-07-00047.
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Favorskaya, M.N., Buryachenko, V.V. (2021). Synchronization Correction Enforced by JPEG Compression in Image Watermarking Scheme for Handheld Mobile Devices. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2765-1_20
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DOI: https://doi.org/10.1007/978-981-16-2765-1_20
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