By Pranab Kumar Dhar, Tetsuya Shimamura

ISBN-10: 3319147994

ISBN-13: 9783319147994

ISBN-10: 3319148001

ISBN-13: 9783319148007

This ebook introduces audio watermarking equipment for copyright security, which has drawn large recognition for securing electronic facts from unauthorized copying. The booklet is split into elements. First, an audio watermarking technique in discrete wavelet rework (DWT) and discrete cosine remodel (DCT) domain names utilizing singular worth decomposition (SVD) and quantization is brought. this technique is powerful opposed to a number of assaults and offers sturdy imperceptible watermarked sounds. Then, an audio watermarking approach in quick Fourier remodel (FFT) area utilizing SVD and Cartesian-polar transformation (CPT) is gifted. this system has excessive imperceptibility and excessive information payload and it presents reliable robustness opposed to a number of assaults. those thoughts permit media proprietors to guard copyright and to teach authenticity and possession in their fabric in various purposes.

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

· Outlines recommendations that supply more desirable functionality by way of imperceptibility, robustness, and information payload

· comprises purposes comparable to info authentication, information indexing, broadcast tracking, fingerprinting, etc.

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

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Each audio signal was presented through headphones. Before conducting the experiment, the procedures were clearly described to the participants, who were trained in evaluating the sound quality effectively. Each participant adjusted the sound volume to their usual listening level. The participants were male and female and of different ages (22–35 years) with normal hearing ability and were suitable candidates for evaluating the sound quality effectively. 2. 0 for all watermarked sounds using the proposed method, indicating that original and watermarked audio signals are perceptually indistinguishable.

Step 8: In order to guarantee the robustness and transparency, the proposed method embeds watermark bit into each of Dix , Diy , Eix , and Eiy of the matrix Si using ui , vi , and ei . 2 Proposed Watermarking Method 41 perceptual components of the audio signal. 2; 2/, where Dix respectively and C1 , C2 , and C3 are the user-defined constants. 2; 2/, where Diy respectively. 2; 2/ D q 0 2 Eix C 0 2 Eiy ; Â20 D tan 1 0 Diy 0 Dix 1 0 Eiy 0 Eix ! 14) ! 2; 2/ of each matrix Si are also preserved to utilize in detection process.

1. Additive white Gaussian noise (AWGN): AWGN is added to the watermarked audio signal. 2. Cropping: 1,000 samples are removed from the front, middle, and end parts of the watermarked audio signal and then these samples are replaced by the watermarked samples attacked with AWGN. 2227 Extracted watermark Fig. 11 Extracted watermark image with NC and BER for the audio signal ‘Classical’ 3. 1 kHz. 4. Requantization: The 16-bit watermarked audio signal is quantized down to 8 bits/sample and again requantized back to 16 bits/sample.

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

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