A natural modification of autocorrelation based video watermarking scheme using ICA for better geometric attack robustness

Authors:
Seong-Whan Kim;Hyun Jin Park;HyunSeong Sung
Affiliations:
Department of Computer Science, University of Seoul, Seoul, Korea;Institute for Neural Computation, UC San Diego, San Diego, La Jolla, CA;Department of Computer Science, University of Seoul, Seoul, Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

Video watermarking hides information (e.g. ownership, recipient information, etc) into video contents. Video watermarking research is classified into (1) extension of still image watermarking, (2) use of the temporal domain features, and (3) use of video compression formats. In this paper, we propose a watermarking scheme to resist geometric attack (rotation, scaling, translation, and mixed) for H.264 (MPEG-4 Part 10 Advanced Video Coding) compressed video contents. Our scheme is based on auto-correlation method for geometric attack, a video perceptual model for maximal watermark capacity, and watermark detection based on natural image statistics. We experimented with the standard images and video sequences and the result shows that our video watermarking scheme is robust against H.264 video compression (average PSNR = 31 dB) and geometric attacks (rotation with 0-90 degree, scaling with 75-200%, and 50%~75% cropping).