Media hash-dependent image watermarking resilient against both geometric attacks and estimation attacks based on false positive-oriented detection

Abstract

The major disadvantage of existing watermarking methods is their limited resistance to extensive geometric attacks. In addition, we have found that the weakness of multiple watermark embedding methods that were initially designed to resist geometric attacks is their inability to withstand the watermark-estimation attacks (WEAs), leading to reduce resistance to geometric attacks. In view of these facts, this paper proposes a robust image watermarking scheme that can withstand geometric distortions and WEAs simultaneously. Our scheme is mainly composed of two components: (i) mesh generation and embedding to resist geometric distortions; and (ii) construction of media hash-based content-dependent watermark (CDW) to resist WEAs. Furthermore, we propose a false positive-oriented watermark detection mechanism, which can be used to determine the existence of a watermark so as to achieve a trade-off between correct detection and false detection. Extensive experimental results obtained using the standard benchmark and WEAs, and comparisons with relevant watermarking methods confirm the excellent performance of our method in improving robustness. To our knowledge, such a thorough evaluation has not been reported in the literature before.

Multilevel histogram shape‐based image watermarking invariant to geometric attacks

“…Histograms constructed from low-frequency component are usually considered more robust against compressing and filtering-like image manipulations. Some schemes suggest the Gaussian low-pass filtering [2,[26][27][28] for this purpose. However, this filtering brings the loss of watermark energy at the watermark extraction phase due to its side effect.…”

E2-Invisible Watermarking for Protecting Intellectual Rights of Medical Images and Records

“…The extracted watermark and reconstructed MI are compared with the original watermark and the original MI respectively and evaluated using the quality metric parameters PSNR, MSE and SSIM. Also the system robustness is verified against various attacks like JPEG compression, Median filter, Wiener filter, and Gaussian filter, Image cropping, Image rotation and Image resize [11] [14]. www.ijacsa.thesai.org…”