Self-Embedding Watermarking Algorithm Under High Tampering Rates

Abstract

A self-embedding watermarking algorithm based on a reference sharing mechanism that has recovery ability under high tampering rates is proposed in this paper. In existing methods, the image recovery ability is often limited under an increasing tampering rate. The proposed method overcomes this limitation by seeking an approximate solution for each character-bit group tampered with. Moreover, the priority assignment of such groups can enhance the accuracy of tampering recovery. Based on this, by using the method proposed in this paper, recovered images always maintain excellent visual quality even at relatively high tampering rates. The experimental results demonstrate the efficacy of the proposed method.

KEYWORDS:

• content recovery
• fragile watermarking
• reference sharing mechanism
• self-embedding
• tampering detection

Acknowledgement

This work was supported in part by the National Natural Science Foundation of China (61702332, 61902239). The authors would like to thank the anonymous reviewers for their valuable suggestions in advance.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61702332,61902239].

Notes on contributors

Zhenyi Zhang

Zhenyi Zhang received the B.S. degree in Communication Engineering from University of Shanghai for Science and Technology, Shanghai, China in 2016. He is currently pursuing the M.S. degree in Instrument and Meter Engineering from University of Shanghai for Science and Technology, Shanghai, China. His research interests include image processing and image data hiding. Email: [email protected]

Heng Yao

Heng Yao received the B. Sc. degree from Hefei University of Technology, China, in 2004, the M. Eng. degree from Shanghai Normal University, China, in 2008, and the Ph. D. degree in signal and information processing from Shanghai University, China, in 2012. Since 2012, he has been with the faculty of the School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, where he is currently an Associate Professor. He has contributed more than 30 international journal papers. His research interests include multimedia security, image processing, and pattern recognition. Corresponding author. Email: [email protected]

Zhaoyang Xiang

Zhaoyang Xiang received the B.S. degree in communication engineering from University for Shanghai Science Technology, Shanghai, China, in 2016. She is currently pursuing the M.S. degree in measuring and testing technologies from University of Shanghai for Science and Technology, China. Her research interests include image processing and data hiding. Email: [email protected]

Fang Cao

Fang Cao received the B.S. degree in applied electronics from Shanghai Normal University, Shanghai, China, in 2002, the M.S. degree in signal and information processing from Shanghai Maritime University, Shanghai, China, in 2004, and the Ph.D. degree in communication and information system from Shanghai University, Shanghai, China, in 2013. Since 2005, she has been with the faculty of the College of Information Engineering, Shanghai Maritime University, where she is currently a Lecturer. Her research interests include image processing, computer vision and multimedia security. Email: [email protected]