By Pranab Kumar Dhar, Tetsuya Shimamura
This e-book introduces audio watermarking tools for copyright defense, which has drawn broad recognition for securing electronic information from unauthorized copying. The e-book is split into elements. First, an audio watermarking approach in discrete wavelet remodel (DWT) and discrete cosine remodel (DCT) domain names utilizing singular price decomposition (SVD) and quantization is brought. this technique is strong opposed to numerous assaults and offers solid 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 information payload and it presents strong robustness opposed to quite a few assaults. those recommendations let media vendors to guard copyright and to teach authenticity and possession in their fabric in numerous functions.
· positive factors new equipment of audio watermarking for copyright defense and possession protection
· Outlines thoughts that offer more suitable functionality by way of imperceptibility, robustness, and knowledge payload
· comprises purposes similar to info authentication, info indexing, broadcast tracking, fingerprinting, etc.
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Additional info for Advances in Audio Watermarking Based on Singular Value Decomposition
5, respectively show the magnitude spectrum of a selected frame for the original and watermarked audio signal ‘Folk’ using the proposed method. 1 Imperceptibility Test Generally, there are two approaches to perform perceptual quality assessment: (i) subjective evaluation test and (ii) objective evaluation test. 1 Subjective Evaluation Test SDG has been used extensively for evaluating the quality of watermarked audio signal. 1. 5 Frequency (Hz) 2 x 104 Fig. 86 out by blind listening tests involving ten participants of different ages (22–35 years) with normal hearing ability.
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.
1 Audio Watermarking Using DFT The discrete Fourier transform (DFT) is a well known and powerful computational tool for performing frequency analysis of discrete time signals. FFT is an efficient algorithm for calculating DFT. It takes a discrete signal in the time domain and transforms this signal into the discrete frequency domain. A significant number of audio watermarking methods have been reported which utilize FFT [30, 32, 50]. Most methods embed watermark information into the magnitude of the FFT components.
Advances in Audio Watermarking Based on Singular Value Decomposition by Pranab Kumar Dhar, Tetsuya Shimamura