Abstract
Principal Components Analysis (PCA) is a valuable technique for dimensionality reduction purposes for huge datasets. Principal components are linear combination of the original variables. The projection of data on this linear subspace keeps the most of the original characteristics. This helps to find robust characteristics for watermarking applications. Most of the PCA based watermarking methods were done in projection space i.e. in eigen image. In this study, different from the other methods, PCA is used to obtain a reference of the cover image by using compression property of PCA. PCA and block-PCA based methods are proposed by using some of the principal vectors in reconstruction. The watermarking is done according to difference of the original and its reference image. The method is compared with Discrete Wavelet Transform (DWT) based approach and its performance against some attacks is discussed.
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References
Schyndel, R.G., Tirkel, A.Z., Osborne, C.F.: A Digital Watermark. In: ICIP 1994. Proceedings of IEEE International Conference on Image Processing, Austin, USA, vol. 2, pp. 86–90. IEEE, Los Alamitos (1994)
Cox, I.J., Kilian, J., Thomson, L., Shamoon, T.: Secure Spread Spectrum Watermarking for Multimedia. IEEE Transactions on Image Processing 6(12), 1673–1687 (1997)
Barni, M., Bartolini, F., Cappellini, V., Piva, A.: A DCT-Domain System for Robust Image Watermarking. Signal Processing 66(3), 357–372 (1998)
Suhail, M.A., Obaidat, M.S.: Digital Watermarking-Based DCT and JPEG Model. IEEE Transactions on Instrumentation and Measurement 52(5), 1640–1647 (2003)
Hsieh, M-S., Tseng, D-C.: Hiding Digital Watermarks Using Multiresolution Wavelet Transform. IEEE Transactions on Industrial Electronics 48(5), 875–882 (2001)
Kundur, D., Hatzinakos, D.: Towards Robust Logo Watermarking Using Multiresolution Image Fusion. IEEE Transactions on Multimedia 1(2), 185–198 (2004)
Chen, B., Wornell, G.W.: Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding. IEEE Transaction on Information Theory 47(4), 1423–1443 (2001)
Pu, Y., Liao, K., Zhou, J., Zhang, N.: A Public Adaptive Watermark Algorithm for Color Images Based on Principal Component Analysis of Generalized Hebb. In: Proceedings of International Conference on Information Acquisition, pp. 484–488 (2004)
Chang, C-C., Lin, P-Y.: A Compression-Based Data Hiding Scheme Using Vector Quantization and Principle Component Analysis. In: International Conference on Cyber Worlds, Tokyo, Japan, pp. 369–375 (2004)
Wang, R., Cheng, Q., Huang, T.: Identify Regions of Interest (ROI) for Video Watermark Embedment with Principle Component Analysis. In: ACM Multimedia, Los Angeles, CA, USA, pp. 459–461. ACM Press, New York (2000)
Kaarna, A., Toivanen, P.: Digital Watermarking of Spectral Images in PCA/Wavelet-transform Domain. In: IGARSS 2003. Proceedings of the International Geoscience and Remote Sensing Symposium, Toulouse, France, vol. VI, pp. 3564–3567 (2003)
Hien, T.D., Chen, Y.-W., Nakao, Z.: The PCA Based Digital watermarking. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS, vol. 2774, pp. 1427–1434. Springer, Heidelberg (2003)
Kang, X., Zeng, W., Huang, J., Zhuang, X., Shi, Y.-Q.: Digital Watermarking Based on Multi-band Wavelet and Principal Component Analysis. In: Proceedings of the SPIE Visual Communications and Image Processing, vol. 5960, pp. 1112–1118 (2005)
Joo, S., Suh, Y., Shin, J., Kikuchi, H.H.: A New Robust Watermark Embedding into Wavelet DC Components. ETRI Journal 24(5), 401–404 (2002)
Liu, J.-L., Lou, D.-C., Chang, M.-C., Tso, H.-K.: A Robust Watermarking scheme Using Self-Reference Image. Computer Standards & Interfaces 28(3), 356–367 (2006)
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Yavuz, E., Telatar, Z. (2007). Digital Watermarking with PCA Based Reference Images. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_92
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DOI: https://doi.org/10.1007/978-3-540-74607-2_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74606-5
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