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