Abstract
In this paper, a robust image watermarking algorithm based on principal component analysis and discrete wavelet transform is proposed for copyright protection. At first, an orientation histogram is obtained from the direction of the feature points of an image identified by a scale invariant feature transform in the proposed watermark embedding scheme. The highest peak of the orientation histogram regarded as the dominant orientation of an image is a start index to divide the image into bins covering 360 degree range of orientation. Moreover, the most important principal components of image coefficients within each bin are obtained after applying principal component analysis. Finally, the copyright watermark is inserted into the wavelet coefficients of these components in quantization steps. Similarly, the proposed watermark detecting scheme follows the above procedure to blindly extract the copyright watermark from a watermarked image. Various attacks are applied to the watermarked images in order to examine the robustness of our algorithm. The experimental results in this paper show that the proposed watermarking algorithm can tolerate JPEG compression, median filtering, Gaussian filtering, sharpening, and rotation attacks.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cox, I.J., Leighton, F.T., Shamoon, T.: Secure Spread Spectrum Watermarking for Multimedia. IEEE Trans. Image Processing 6(12), (1997)
Podilchuk, C.I., Zeng, W.: Image-Adaptive Watermarking Using Visual Models. IEEE J. Select. Areas Commun. 16(4), 525–539 (1998)
Chen, B., Wornell, G.W.: Quantization Index Modulation: A class of provably good methods for digital watermarking and information embedding. IEEE Trans. Information Theory 47(4), 1423–1443 (2001)
Lin, E.T., Delp, E.J.: Review of fragile image watermarks. In: Proc. of ACM Multimedia and Security Workshop, pp. 25–29 (October 1999)
Wong, P.W., Memon, N.: Secret and public key image watermarking schemes for image authentication and ownership verification. IEEE Trans. Image Processing 10(10), 1593–1601 (2001)
Bao, P., Ma, X.: Image adaptive watermarking using wavelet domain singular value decomposition. IEEE Trans. Circuits Syst. Video Technol. 15(1), 96–102 (2005)
Bi, N., Sun, Q., Huang, D., Yang, Z., Huang, J.: Robust image watermarking based on multiband wavelets and empirical mode decomposition. IEEE Trans. Image Processing 16(8), 1956–1966 (2007)
Licks, V., Jordan, R.: Geometric Attacks on Image Watermarking Systems. IEEE Multimedia Magazine 12(3), 68–78 (2005)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Computer Vision 60(2), 91–110 (2004)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Analysis and Machine Intelligence 27(10), 1615–1630 (2005)
Cohen, A., Daubechies, I., Feauveau, J.C.: Biorthogonal bases of compactly supported wavelets. Commun. Pure and Applied Mach. 45(5), 485–560 (1992)
Fabien, A., Petitcolas, P.: Watermarking schemes evaluation. IEEE Signal Processing 17(5), 58–64 (2000)
Cox, I.J., Miller, M.L., Bloom, J.A.: Digital Watermarking. Morgan Kaufman, San Francisco (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tsai, JS., Huang, WB., Li, PH., Chen, CL., Kuo, YH. (2008). Robust Digital Image Watermarking Based on Principal Component Analysis and Discrete Wavelet Transform. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_52
Download citation
DOI: https://doi.org/10.1007/978-3-540-89796-5_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89795-8
Online ISBN: 978-3-540-89796-5
eBook Packages: Computer ScienceComputer Science (R0)