A Robust Image Watermarking Approach Using Cycle Variational Autoencoder
Joint Authors
Wang, Hu
Wei, Qiang
Zhang, Gongxuan
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-22
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
With the rapid development of Internet and cloud storage, data security sharing and copyright protection are becoming more and more important.
In this paper, we introduce a robust image watermarking algorithm for copyright protection based on variational autoencoder networks.
The proposed image watermarking embedding and extracting network consists of three parts: encoder subnetwork, decoder subnetwork, and detector subnetwork.
In the training process, the encoder and decoder subnetworks learn a robust image representation model and further implement the embedding of 1-bit watermark image to the cover image.
Meanwhile, the detector subnetwork learns to extract the 1-bit watermark image from the embedding image.
Experimental results demonstrate that the watermarked images generated by the proposed algorithm have better visual effects and are more robust against geometric and noise attacks than traditional approaches in the transform domain.
American Psychological Association (APA)
Wei, Qiang& Wang, Hu& Zhang, Gongxuan. 2020. A Robust Image Watermarking Approach Using Cycle Variational Autoencoder. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1208802
Modern Language Association (MLA)
Wei, Qiang…[et al.]. A Robust Image Watermarking Approach Using Cycle Variational Autoencoder. Security and Communication Networks No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1208802
American Medical Association (AMA)
Wei, Qiang& Wang, Hu& Zhang, Gongxuan. A Robust Image Watermarking Approach Using Cycle Variational Autoencoder. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1208802
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208802