Robust DFT watermarking method with gray component replacement masking

Poljičak, Ante; Donevski, Davor; Jelušić, Petar Branislav; Cigula, Tomislav

doi:10.1007/s11042-022-12756-9

Cited by 5 publications

(1 citation statement)

References 30 publications

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“…More recently, Ref. [96] proposed a novel discrete Fourier watermarking method based on gray component replacement (GCR) masking for printed images. The watermark was concealed in the amplitude coefficients in the Fourier domain.…”

Section: Discrete Fourier Transform (Dft)mentioning

confidence: 99%

Image Watermarking between Conventional and Learning-Based Techniques: A Literature Review

et al. 2022

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Currently, most transactions and exchanges are conducted through the Internet thanks to technological tools, running the risk of the falsification and distortion of information. This is due to the massive demand for the virtual world and its easy access to anyone. Image watermarking has recently emerged as one of the most important areas for protecting content and enhancing durability and resistance to these kinds of attacks. However, there is currently no integrated technology able to repel all possible kinds of attacks; the main objective of each technology remains limited to specific types of applications, meaning there are multiple opportunities to contribute to the development of this field. Recently, the image watermarking field has gained significant benefits from the sudden popularity of deep learning and its outstanding success in the field of information security. Thus, in this article, we will describe the bridge by which the watermarking field has evolved from traditional technology to intelligent technologies based on deep learning.

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Section: Discrete Fourier Transform (Dft)mentioning

confidence: 99%