Spatially localized image-dependent watermarking for statistical invisibility and collusion resistance

We develop a novel video watermarking framework based on the collusion-resistant design rules formulated in a companion paper. We propose to employ a spatially-localized image dependent approach to create a watermark whose pairwise frame correlations approximate those of the host video. To characterize the spread of its spatially-localized energy distribution, the notion of a watermark footprint is introduced. Then we explain how a particular type of image dependent footprint structure, comprised of subframes centered around a set of visually significant anchor points, can lead to two advantageous results: pairwise watermark frame correlations that more closely match those of the host video for statistical invisibility, and the ability to apply image watermarks directly to a frame sequence without sacrificing collusion-resistance. In the ensuing overview of the proposed video watermark, two new ideas are put forward: synchronizing the subframe locations using visual content rather than structural markers and exploiting the inherent spatial diversity of the subframe-based watermark to improve detector performance. Simulation results are presented to show that the proposed scheme provides improved resistance to linear frame collusion, while still being embedded and extracted using relatively low complexity frame-based algorithms.

[1]  Thierry Pun,et al.  Attack modelling: towards a second generation watermarking benchmark , 2001, Signal Process..

[2]  Gabriela Csurka,et al.  Countermeasures for unintentional and intentional video watermarking attacks , 2000, Electronic Imaging.

[3]  Ingemar J. Cox,et al.  Secure spread spectrum watermarking for multimedia , 1997, IEEE Trans. Image Process..

[4]  K. E. Tait,et al.  Image recovery using the anisotropic diffusion equation , 1996, IEEE Trans. Image Process..

[5]  Ton Kalker,et al.  Video watermarking system for broadcast monitoring , 1999, Electronic Imaging.

[6]  Bernd Girod,et al.  Watermarking of uncompressed and compressed video , 1998, Signal Process..

[7]  C.-C. Jay Kuo,et al.  Digital Image Watermarking in Regions of Interest , 1999, PICS.

[8]  Soo-Chang Pei,et al.  Image normalization for pattern recognition , 1995, Image Vis. Comput..

[9]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Karen Su,et al.  Digital video watermarking principles for resistance to collusion and interpolation attacks , 2001 .

[11]  L.J. Karam,et al.  Automatic detection and extraction of perceptually significant visual features , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[12]  Thierry Pun,et al.  Attack modelling : towards a second generation benchmark , 2001 .

[13]  Klara Nahrstedt,et al.  Watermarking methods for MPEG encoded video: towards resolving rightful ownership , 1998, Proceedings. IEEE International Conference on Multimedia Computing and Systems (Cat. No.98TB100241).

[14]  Deepa Kundur,et al.  Statistical invisibility for collusion-resistant digital video watermarking , 2005, IEEE Transactions on Multimedia.

[15]  Jiri Fridrich,et al.  Robust bit extraction from images , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[16]  Jean-Francois Delaigle,et al.  A Block Based Watermarking Technique for MPEG2 Signals: Optimization and Validation on Real Digital TV Distribution Links , 1998, ECMAST.

[17]  Zixiang Xiong,et al.  Multiresolution watermarking for images and video , 1999, IEEE Trans. Circuits Syst. Video Technol..

[18]  Jessica J. Fridrich.  Visual hash for oblivious watermarking , 2000, Electronic Imaging.

[19]  Peter Eisert,et al.  Digital watermarking of MPEG-4 facial animation parameters , 1998, Comput. Graph..

[20]  Ahmed H. Tewfik,et al.  Multiresolution scene-based video watermarking using perceptual models , 1998, IEEE J. Sel. Areas Commun..

[21]  Thierry Pun,et al.  A Stochastic Approach to Content Adaptive Digital Image Watermarking , 1999, Information Hiding.

[22]  Rama Chellappa,et al.  A new approach to image feature detection with applications , 1996, Pattern Recognit..

[23]  Nuno Vasconcelos,et al.  Statistical models of video structure for content analysis and characterization , 2000, IEEE Trans. Image Process..

[24]  Jpeg Image Compression Faq, Part 1/2 , .

[25]  Deepa Kundur,et al.  Attack characterization for effective watermarking , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[26]  Bernd Girod,et al.  Capacity of digital watermarks subjected to an optimal collusion attack , 2000, 2000 10th European Signal Processing Conference.

[27]  Deepa Kundur,et al.  Diversity and attack characterization for improved robust watermarking , 2001, IEEE Trans. Signal Process..

[28]  Markus G. Kuhn,et al.  Attacks on Copyright Marking Systems , 1998, Information Hiding.

[29]  Bijan G. Mobasseri.  Exploring CDMA for watermarking of digital video , 1999, Electronic Imaging.

[30]  Thierry Pun,et al.  Robust template matching for affine resistant image watermarks , 2000, IEEE Trans. Image Process..

[31]  Jan Vandewege,et al.  How to achieve robustness against scaling in a real-time digital watermarking system for broadcast monitoring , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[32]  Philip Ogunbona,et al.  Region-Based Watermarking for Images , 1999, ISW.

[33]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .