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In this paper, we introduce a robust image watermarking method based on bi-dimensional empirical mode decomposition (BEMD) against geometric distortion. Based on the characteristics of the image theory and human visual system, the proposed method makes use of orthogonal properties of empirical mode decomposition to achieve the BEMD transform on the image. The image is decomposed into a series of IMFs and residue which contain the different frequency parts of the image. So the watermark is adaptively weighed to the different positions of the middle frequency IMF region. The method makes use of the multi-scale analysis characteristics of image BEMD theory and the person’s sense of vision and shows excellent advantage against shearing attack. The method could show the watermark clearly when half of the image has been cut. Experimental results show this method excellent robustness for image shearing. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

In this paper, a robust image watermarking method in two-dimensional space/spatial-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The one-dimensional S transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signals by choosing scalable local time windows. The watermark embedded in the 1D S transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

In this paper, we introduce a 3D wavelet transform based robust watermark casting scheme against shearing attack for digital images. Based on the characteristics of the image theory and human visual system, the proposed method make use of the there-dimensional video wavelet transform to split the image to a sense of image videos and the watermark is adaptively weighed to the different positions of the middle frequency region. The method makes use of the characteristics of image two-dimensional wavelet transform and the person's sense of vision and shows excellent advantage against shearing attack. The method could show the watermark clearly when half of the image has been cut. Experimental results show this method excellent robustness for image shearing. The goal of this paper is to achieve robust digital image watermark against shearing. The algorithm achieves the robustness to the shearing attacks.

In this paper, a robust digital watermarking method against shearing based on orthogonal function system is introduced. The proposed method makes use of the complete generalized orthogonal properties of Haar orthogonal function system to achieve the piece-based orthogonal transform on the image. The significant middle frequently coefficients in the transformation matrix are picked up, based on characteristics of the image visual system and the Haar orthogonal transform. The watermark is adoptively weighed to the middle frequently matrix. The method improves the validity of watermarking and shows excellent advantage against shearing attack. Experimental results show that the Haar orthogonal function system based watermark approach can provide an excellent protection under geometric attacks.