Abstract:
Watermarking in computer or information security, is a technique that embeds the copyright
information of digital signals or digital identifier in the respective signals of the
host to provide authenticity who the copyright owners are or to track from where the
signal is originating. In general, an efficient watermarking technique must give two
features: robustness and perceptual imperceptibility. In this thesis, a watermarking
technique is proposed based on a new combination of Fast Curvelet Tansform (FCT),
Robust Principal Component Analysis (RPCA) and Singular Value Decomposition
(SVD). The gray-scale watermark logo is scrambled using Generalized Arnold Transform
(GAT) to enhance the robustness and security. The original image is decomposed
to low rank and sparse components using RPCA; the curvelet coefficients are obtained
using FCT via Unequally-Spaced Fast Fourier Transforms (USFFT) to embed the processed
watermark using SVD into the color image. The robustness and imperceptibility
of the proposed technique is verified against a variety of processing operations (noise,
filtering) and geometric attacks (crop, resize, projection etc.). In curvelet transform,
fewer coefficients contain the most energy, also giving optimally sparse representation
of the significant image features and edges that helps in efficient recovery of the
embedded watermark even after severe image degradation. To verify the signicance
of the proposed technique it is compared with state of the art existing watermarking
technique. The quantitative and visual simulation results reveal that the proposed watermarking
technique is efficient and provides high tolerance against geometric as well
as normal image processing attacks as compared to state of art existing watermarking
technique.
