Video watermark detection with controllable performance with and without knowledge of watermark location

ABSTRACT

In this paper, we build a theoretical framework for video watermark detection based on a likelihood ratio test. This framework is used to develop two different video watermark detection algorithms; one detects the watermark only from watermarked coefficients and one detects the watermark from all the ac coefficients in the video. These algorithms can be used in different video watermark detection applications where the detector knows and does not know the precise location of watermarked coefficients. Both watermark detection schemes have controllable detection performance, thus, the error rate of the detector can be maintained regardless of the video sequence if the video is long and the detector response latency can be arbitrary. Furthermore, the detector can maintain the same detection performance after attacks by using more frames to obtain its detection response. Our simulation results show that we achieve the desired detection performance in Monte Carlo trials. We also demonstrate the robustness of our proposed algorithm to several different attacks.

REFERENCES

• 1: H.264 reference software group. http://iphome.hhi.de/suehring/tml/, 2006.
• 2: K. A. Birney and T. R. Fischer. On the modeling of DCT and subband image data for compression. IEEE Transactions on Image Processing, 4(2):186--193, February 1995.
• 3: R. H. Jonsson. Adaptive subband coding of video using probability distribution models. PhD thesis, Georgia Institute of Technology, 1994.
• 4: M. Noorkami and R. M. Mersereau. Digital video watermarking in P-frames. In Proceedings of SPIE - The International Society for Optical Engineering, volume 6505, San Jose, CA, USA, January 2007.
• 5: M. Noorkami and R. M. Mersereau. A framework for robust watermarking of H.264-encoded video with controllable detection performance. IEEE Transactions on Information Forensics and Security, 2(1):14--23, March 2007.
• 6: Harry L. Van Trees, Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise, Krieger Publishing Co., Inc., Melbourne, FL, 1992
• 7: A. B. Watson. DCT quantization matrices visually optimized for individual images. In Proceedings of the SPIE - The International Society for Optical Engineering, volume 1913, pages 202--216, San Jose, CA, USA, February 1993.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.9 Applications

General Terms:
Algorithms, Performance, Theory

Keywords:
H.264, controllable performance, likelihood ratio test, video watermark detection, video watermarking