Download e-book for iPad: Digital Audio Watermarking Techniques and Technologies: by Nedeljko Cvejic, Tapio Seppanen

By Nedeljko Cvejic, Tapio Seppanen

ISBN-10: 1599045133

ISBN-13: 9781599045139

ISBN-10: 159904515X

ISBN-13: 9781599045153

"Digital audio watermarking has been proposed as a brand new and replacement technique to implement highbrow estate rights and safeguard electronic audio from tampering. electronic Audio Watermarking strategies and applied sciences: purposes and Benchmarks is a entire compilation of the main theoretical frameworks, examine findings, and sensible functions. With inclusive assurance of the main authoritative study within the sector, electronic Audio Watermarking concepts and applied sciences: purposes and Benchmarks will function an essential connection with researchers and practitioners in various disciplines, together with engineering, details know-how, and electronic audio. With price to a various variety of clients, this best Reference resource matches libraries in different settings."

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Additional resources for Digital Audio Watermarking Techniques and Technologies: Applications and Benchmarks

Sample text

The secret factor a in equation (45) controls the high energy blocks distribution. Different aresults in different high energy blocks distribution. A lower value for a decreases the thresholds for high energy areas, thus more areas are treated as high energy areas. Although this provides more room to embed the watermarks, it reduces the system robustness since some high energy areas may become unstable after common signal processing or attacks. A higher a, on the other hand, increases such threshold, thus decreasing the number of high energy areas.

The input audio is segmented into overlapping frames. Each frame is decomposed by the DWPT into 25 sub bands that approximate the auditory critical bands as illustrated in Figure 19. Signal energy in each band is computed in the wavelet domain to provide the Bark spectrum energy. Tonality is estimated in each band to determine the extent the signal in that band Spread Spectrum for Digital Audio Watermarking e. f. g. h. is noise-like or tone-like. Shifted bark energy is calculated by scaling the bark energy according to the tonality factor.

D. e. f. g. Psychoacoustic Model A psychoacoustic model is applied to determine the masking thresholds for each frame in order to render the inserted data inaudible. The data are spread by a pseudo random sequence (PN sequence). Synchronization codes are attached to the spread data thus producing the final watermarks to be embedded. Watermark embedding into the original audio is conditional on the masking thresholds constraints. If the watermark is embedded in the transform domain then inverse transform is applied on the watermarked frame to convert the watermarked audio back to the time domain.

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Digital Audio Watermarking Techniques and Technologies: Applications and Benchmarks by Nedeljko Cvejic, Tapio Seppanen

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