A New Efficient Robustness Evaluation Approach for Video Watermarking based on Crowdsourcing

Asma Kerbiche, Saoussen Ben Jabra, Ezzeddine Zagrouba, Vincent Charvillat

2016

Abstract

Signature robustness is the most important criteria that must verify a watermarking approach. However, existing watermarking evaluation protocols always tested simple attacks like rotation, cropping, and compression but did not consider many dangerous attacks such as camcording which is more and more used for videos. In this paper, a new robustness evaluation approach for video watermarking is proposed. It is based on on-line attack’s game using crowdsourcing technique. In fact, the proposed game is provided to different users who will try to destruct an embedded signature by applying one or many combined attacks on a given marked video. Switch the choice of the users, the most important attacks can be selected. In more, users must not destroy the visual quality of the marked video to evaluate the tested watermarking approach. Experimental results show that the proposed approach permits to evaluate efficiently the robustness of any video watermarking. In addition, obtained results verify that camcording attack is very important in video watermarking evaluation process.

Paper Citation

in Harvard Style

Kerbiche A., Ben Jabra S., Zagrouba E. and Charvillat V. (2016). A New Efficient Robustness Evaluation Approach for Video Watermarking based on Crowdsourcing . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 167-173. DOI: 10.5220/0005726201670173

in Bibtex Style

@conference{visapp16,
author={Asma Kerbiche and Saoussen Ben Jabra and Ezzeddine Zagrouba and Vincent Charvillat},
title={A New Efficient Robustness Evaluation Approach for Video Watermarking based on Crowdsourcing},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={167-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005726201670173},
isbn={978-989-758-175-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - A New Efficient Robustness Evaluation Approach for Video Watermarking based on Crowdsourcing
SN - 978-989-758-175-5
AU - Kerbiche A.
AU - Ben Jabra S.
AU - Zagrouba E.
AU - Charvillat V.
PY - 2016
SP - 167
EP - 173
DO - 10.5220/0005726201670173