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Dhar P.K., Shimamura T. Advances in Audio Watermarking Based on Singular Value Decomposition

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Dhar P.K., Shimamura T. Advances in Audio Watermarking Based on Singular Value Decomposition
Springer, 2015. — 75 p.
In recent years, due to the rapid development of the Internet and multimedia technology, the transmission and distribution of multimedia data have become an extremely simple task. This has become a serious threat for multimedia content owners. Thus, there is a significant interest for copyright protection of multimedia data. Digital watermarking has drawn extensive attention for copyright protection of multimedia data. It is a process of embedding watermarks into the multimedia data to show authenticity and ownership. This technique has several applications such as copyright protection, data authentication, fingerprinting, data indexing, and broadcast monitoring. This book introduces two watermarking methods for copyright protection. An audio watermarking method in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains using singular value decomposition (SVD) and quantization is presented. In this method, initially the original audio is segmented into nonoverlapping frames. DWT is applied to each frame and detail coefficients are arranged into a one-dimensional matrix formation. DCT is performed on this matrix and the obtained DCT coefficients are reshaped. SVD is applied to the DCT coefficients and watermark information is then embedded into the highest singular value by quantization. Watermark information is extracted by comparing the largest singular value of the DCT coefficients obtained from DWT subbands of each original and attacked watermarked audio frame. This method is robust against various attacks and provides good imperceptible watermarked sounds. An audio watermarking method in fast Fourier transform (FFT) domain using SVD and Cartesian-polar transform (CPT) is presented. In this method, initially the original audio is segmented into nonoverlapping frames. FFT is applied to each frame and low-frequency FFT coefficients are selected. SVD is applied to the selected FFT coefficients of each frame represented in a matrix form. The highest two singular values of each frame are selected. The selected singular values are assumed as the components of polar coordinate system and are transformed into the components of Cartesian coordinate system. Watermark information is embedded into each of these Cartesian components using an embedding function. Watermark information is extracted by comparing the Cartesian components of the largest two singular values obtained from the low-frequency FFT coefficients of each original and attacked watermarked audio frame. This method has high data payload and it provides good robustness against various attacks. The performance of the proposed watermarking methods is evaluated and, finally, compared with the state-of-the-art methods. Simulation results indicate that the proposed audio watermarking methods outperform the state-of-the-art methods in terms of robustness, imperceptibility, and data payload. These results verify the effectiveness of the proposed methods as a suitable candidate for copyright protection of audio signal.
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