Abstract

This paper presents a new rotation, scale and translation invariant blind watermarking algorithm that combines discrete Tchebichef transform (DTT) with a singular value decomposition (SVD) scheme. The proposed method overcomes false-positive problem, and diagonal line problem in the extracted watermark. The DTT coefficients of the image are arranged in a wavelet-like hierarchical sub-band scheme which generates LL (approximation), HL (vertical), LH (horizontal) and HH (diagonal) sub-bands. SVD is applied to all DTT sub-bands in order to decompose it into lower triangular, diagonal and upper triangular components. After applying SVD, the principal components of the watermark are embedded into the diagonal components of each DTT sub-band using appropriate scale factor. Further improvement of robustness is achieved due to the combination of Arnold transform and permutation operation which scrambles the watermark. Embedding the principal component rather than diagonal component of the watermark makes the algorithm robust to false-positive and ambiguity attacks. The visible diagonal line problem in the extracted watermark is also successively eliminated due to the embedment of principal components of watermark rather than the watermark. In addition to this, our scheme shows better robustness to most of the signal processing attacks. A suitable reverse process is applied to extract the watermark at the decoder output. The proposed method is also combined with scale-invariant feature transform (SIFT) at the output stage of the encoder. The geometrical attacks such as rotation, scale and translation are restored back using the feature mapping process owing to SIFT at the decoder input. Finally, the watermark can be recovered by applying extraction algorithm at the decoder output. Simulation on various kinds of standard test images demonstrated that the proposed methods shows a better trade-off against imperceptibility and robustness to common attacks, geometrical attacks as well as combined attacks.

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