Deep Learning-Based Watermarking Techniques Challenges: A Review of Current and Future Trends

被引:5
作者
Ben Jabra, Saoussen [1 ]
Ben Farah, Mohamed [2 ]
机构
[1] Univ Sousse, Natl Engn Sch Sousse, LimT Lab, Sousse, Tunisia
[2] Birmingham City Univ, Birmingham B4 7XG, England
基金
英国科研创新办公室;
关键词
Watermarking; Deep learning; Neural network; Robustness; Embedding; Extraction; ROBUST VIDEO WATERMARKING; IMAGE WATERMARKING; ALGORITHM; SCHEME; BLIND; DOMAIN; DCT; ROTATION; ATTACKS;
D O I
10.1007/s00034-024-02651-z
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The digital revolution places great emphasis on digital media watermarking due to the increased vulnerability of multimedia content to unauthorized alterations. Recently, in the digital boom in the technology of hiding data, research has been tending to perform watermarking with numerous architectures of deep learning, which has explored a variety of problems since its inception. Several watermarking approaches based on deep learning have been proposed, and they have proven their efficiency compared to traditional methods. This paper summarizes recent developments in conventional and deep learning image and video watermarking techniques. It shows that although there are many conventional techniques focused on video watermarking, there are yet to be any deep learning models focusing on this area; however, for image watermarking, different deep learning-based techniques where efficiency in invisibility and robustness depends on the used network architecture are observed. This study has been concluded by discussing possible research directions in deep learning-based video watermarking.
引用
收藏
页码:4339 / 4368
页数:30
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