By Topic

A Framework for Robust Watermarking of H.264-Encoded Video With Controllable Detection Performance

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Maneli Noorkami ; Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA ; Russell M. Mersereau

As H.264 digital video becomes more prevalent, the need for copyright protection and authentication methods that are appropriate for this standard will emerge. This paper proposes a robust watermarking algorithm for H.264. We employ a human visual model adapted for a 4 times 4 discrete cosine transform block to increase the payload and robustness while limiting visual distortion. A key-dependent algorithm is used to select a subset of the coefficients that have visual watermarking capacity. Furthermore, the watermark is spread over frequencies and within blocks to avoid error pooling. This increases the payload and robustness without noticeably changing the perceptual quality. We embed the watermark in the coded residuals to avoid decompressing the video; however, we detect the watermark from the decoded video sequence in order to make the algorithm robust to intraprediction mode changes. We build a theoretical framework for watermark detection based on a likelihood ratio test. This framework is used to obtain optimal video watermark detection with controllable detection performance. Our simulation results show that we achieve the desired detection performance in Monte Carlo trials. We demonstrate the robustness of our proposed algorithm to several different attacks

Published in:

IEEE Transactions on Information Forensics and Security  (Volume:2 ,  Issue: 1 )