Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering

On the Robustness with Secure Video Watermarking Data via Compressed Sensing

Authors
L.F. Cai, H.M. Zhao, Y.M. Fang, W.G. Wei
Corresponding Author
L.F. Cai
Available Online July 2015.
DOI
10.2991/aiie-15.2015.123How to use a DOI?
Keywords
robustness; watermarking; compressed sensing; security
Abstract

In video information hiding processes, the security and robustness of watermarking data are two important performances. Based on the generation of robust watermarking signal, this paper proposes a secure video information hiding solution for protecting fingerprint content. In our proposed method, construction of the fingerprint watermarking signal is obtained by the compressed sensing (CS) measurements relies on the knowledge of the measurement matrix used for sensing, in which the pseudo-random sensing matrix can offer a natural method for the secret key. Our analysis and results indicate that the proposed fingerprint hiding system can possess a better robustness, and the watermarking data has a higher security.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-70-7
ISSN
1951-6851
DOI
10.2991/aiie-15.2015.123How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - L.F. Cai
AU  - H.M. Zhao
AU  - Y.M. Fang
AU  - W.G. Wei
PY  - 2015/07
DA  - 2015/07
TI  - On the Robustness with Secure Video Watermarking Data via Compressed Sensing
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 453
EP  - 456
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.123
DO  - 10.2991/aiie-15.2015.123
ID  - Cai2015/07
ER  -