A motion location based video watermarking scheme using ICA to extract dynamic frames
In this paper, we propose a novel video watermarking scheme based on motion location. In the proposed scheme, independent component analysis is used to extract a dynamic frame from two successive frames of original video, and the motion is located by using the variance of 8 × 8 block in the extracted dynamic frame. Then according to the located motion, we choose a corresponding region in the former frame of the two successive frames, where watermark is embedded by using the quantization index modulation algorithm. The procedure above is repeated until each frame of the video (excluding the last one) is watermarked. The simulations show that the proposed scheme has a good performance to resist Gaussian noising, MPEG2 compression, frame dropping, frame cropping, etc.
KeywordsVideo watermarking Motion location ICA QIM Watson’s perceptual model
This work is supported by Program for New Century Excellent Talents in University Education Ministry of China (NCET-05-0582), the Excellent Youth Scientist Award Foundation of Shandong Province (No. 2007BS01023; No. 2007BS01006), the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20050422017), National Natural Science Foundation of China (No. 60872024), Cultivation Fund of the Key Scientific and Technical Innovation Project (NO. 708059) and Natural Science Foundation of Shandong Province (No. Y2007G04).
- 5.Sun J, Liu J (2005) A temporal desynchronization resilient video watermarking scheme based on independent component analysis. IEEE international conference on image processing (ICIP 2005) 1:265–268Google Scholar
- 6.Zhang J, Li J, Zhang L (2001) Video watermark technique in motion vector. Proceedings of XIV Brazilian symposium on computer graphics and image processing: 179–182Google Scholar
- 8.Liu J, Nie K, He Z (2001) Blind separation by redundancy reduction in a recurrent neural network. Chin J Electron 10(3):415–419Google Scholar
- 12.Li Q, Cox IJ (2005) Using perceptual models to improve fidelity and provide invariance to valumetric scaling for quantization index modulation watermarking. IEEE international conference acoustics, speech and signal processing (ICASSP 2005) 2:1–4 Google Scholar
- 15.Watson AB (1993) DCT quantization matrices visually optimized for individual images. human vision, visual processing, and digital display IV. Proc SPIE 1913:202–216. doi: 10.1117/12.152694
- 16.Cox IJ, Miller ML, Bloom JA (2001) Digital watermarking. Morgan Kaufmann, San MateoGoogle Scholar