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Among them, SVD has obtained a wide popularity due to its own intrinsic properties. The Singular Value Decomposition is a powerful numerical tool for factorizing matrices that has been formerly applied to various signal processing applications. The essential characteristic of the SVD is the slight variation of singular values when a wide variety of image processing operations and geometric transforms are applied to the matrix. The SVD transform began to be used extensively in various data hiding schemes especially for devising robust watermarking algorithms resistant to geometric attacks. Indeed, many of the existing SVD-based techniques insert the secret information into the singular values of the cover signal, which implies a high r...