Machine Learning-Based Digital Watermarking Design
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 3972
Special Issue Editor
Interests: image processing; signal processing; hardware design; digital hologram; NPU; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Until recently, the study of watermarking technology for 2D images has been mainly based on signal processing. In general, watermarked content and information are exposed to malicious attacks designed to damage or remove watermark information or non-malicious attacks during processing essential to storing or distributing content. Watermark embedding can be performed algorithmically or deterministically, but watermark extraction often cannot. More specifically, since the signal or information that has been attacked is not a signal predicted when the algorithmic extraction method was devised, it may not be possible to guarantee that the watermark inserted by the algorithmic extraction method can be extracted. As one method to overcome this limitation, a technique for performing watermarking with a neural network has been recently proposed.
Recently, machine learning-based digital watermarking methods have been actively studied. The embedding algorithm of digital watermarking based on machine learning allows the watermark to be inserted through learning so that the extracting algorithm can easily extract the watermark while ensuring invisibility. In addition, digital watermarking based on machine learning can improve the invisibility and robustness of watermarking technology by including various malicious and non-malicious attacks in the learning of neural networks.
Prof. Dr. Young-Ho Seo
Guest Editor
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Keywords
- machine learning-based digital watermarking design
- deep learning-based digital watermarking
- deep neural network design for digital watermarking
- attack modeling for machine learning-based watermarking
- machine learning-based content (information) security
- machine learning-based stenography technology
- hardware or software implementation (development) of machine learning-based watermarking
