Download e-book for iPad: Advances in Audio Watermarking Based on Singular Value by Pranab Kumar Dhar, Tetsuya Shimamura

By Pranab Kumar Dhar, Tetsuya Shimamura

ISBN-10: 3319147994

ISBN-13: 9783319147994

ISBN-10: 3319148001

ISBN-13: 9783319148007

This e-book introduces audio watermarking tools for copyright safeguard, which has drawn vast realization for securing electronic info from unauthorized copying. The booklet is split into components. First, an audio watermarking strategy in discrete wavelet rework (DWT) and discrete cosine rework (DCT) domain names utilizing singular worth decomposition (SVD) and quantization is brought. this technique is strong opposed to a number of assaults and gives reliable imperceptible watermarked sounds. Then, an audio watermarking strategy in quick Fourier remodel (FFT) area utilizing SVD and Cartesian-polar transformation (CPT) is gifted. this system has excessive imperceptibility and excessive info payload and it offers sturdy robustness opposed to a variety of assaults. those recommendations let media proprietors to guard copyright and to teach authenticity and possession in their fabric in quite a few purposes.

· positive factors new equipment of audio watermarking for copyright safeguard and possession protection

· Outlines recommendations that offer more desirable functionality when it comes to imperceptibility, robustness, and knowledge payload

· contains functions similar to info authentication, information indexing, broadcast tracking, fingerprinting, etc.

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Extra info for Advances in Audio Watermarking Based on Singular Value Decomposition

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4 summarizes the robustness results of the proposed method for the audio signals ‘Pop’, ‘Jazz’, and ‘Folk’. 96 and the BER values are all below 4 %, indicating the high robustness of our proposed method against different attacks. 3 Error Analysis We analyzed the performance of the proposed method in terms of the false positive error (FPE) and false negative error (FNE). It is difficult to give an exact probabilistic model for an FPE and an FNE. 3203 based on a binomial probability distribution similar to that in [8] to estimate the probability of an FPE and an FNE for our proposed method.

This is because the low frequency FFT coefficients correspond to the energy of the most perceptually significant regions in an audio signal and slight variations of the Cartesian components of the largest singular values do not significantly affect the quality of the signal. Experimental results indicate that the proposed watermarking method is highly robust against various signal processing attacks. In addition, the proposed method has a high data payload. Moreover, it outperforms state-of-the-art audio watermarking methods in terms of imperceptibility, robustness, and data payload.

Let k be the total number of watermark bits and h be the total number of matching bits. 8) hDd0:8ke  à k where is the binomial coefficient. We observed that Eq. 8 is independent of h the BER. This indicates that an FPE is independent of the type of attacks. 1 0 0 20 40 60 80 100 k Fig. 12 Probability of FPE for various values of k select k D 1;024, by substituting the value of h, Eq. 8 gives PFPE D 2:6209 10 88 . 0; 100, which indicates that the FPE probability approaches 0 when k is larger than 20.

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Advances in Audio Watermarking Based on Singular Value Decomposition by Pranab Kumar Dhar, Tetsuya Shimamura

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