Robust Digital Image Watermarking Based on Principal Component Analysis and Discrete Wavelet Transform

Authors:
Jen-Sheng Tsai;Win-Bin Huang;Po-Hung Li;Chao-Lieh Chen;Yau-Hwang Kuo
Affiliations:
Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C.;Department of Electronic Engineering, National Kaohsiung First University of Science and Technology, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C.
Venue:
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2008

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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.