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Advances in Audio Watermarking Based on Singular Value Decomposition
This book introduces audio watermarking methods for copyright protection, which has drawn extensive attention for securing digital data from unauthorized copying. The book is divided into two parts. First, an audio watermarking method in discrete wavelet transform (DWT) and discrete cosine transform...
| Clasificación: | Libro Electrónico |
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| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edición: | 1st ed. 2015. |
| Colección: | SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-14800-7 | ||
| 003 | DE-He213 | ||
| 005 | 20220116043016.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150330s2015 sz | s |||| 0|eng d | ||
| 020 | |a 9783319148007 |9 978-3-319-14800-7 | ||
| 024 | 7 | |a 10.1007/978-3-319-14800-7 |2 doi | |
| 050 | 4 | |a TK5102.9 | |
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| 100 | 1 | |a Dhar, Pranab Kumar. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Advances in Audio Watermarking Based on Singular Value Decomposition |h [electronic resource] / |c by Pranab Kumar Dhar, Tetsuya Shimamura. |
| 250 | |a 1st ed. 2015. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2015. | |
| 300 | |a XVIII, 58 p. 26 illus., 18 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |x 2191-7388 | |
| 505 | 0 | |a Introduction -- Background Information -- DWT-DCT-Based Audio Watermarking Using SVD -- FFT-Based Audio Watermarking Using SVD and CPT -- Conclusions. | |
| 520 | |a This book introduces audio watermarking methods for copyright protection, which has drawn extensive attention for securing digital data from unauthorized copying. The book is divided into two parts. First, an audio watermarking method in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains using singular value decomposition (SVD) and quantization is introduced. This method is robust against various attacks and provides good imperceptible watermarked sounds. Then, an audio watermarking method in fast Fourier transform (FFT) domain using SVD and Cartesian-polar transformation (CPT) is presented. This method has high imperceptibility and high data payload and it provides good robustness against various attacks. These techniques allow media owners to protect copyright and to show authenticity and ownership of their material in a variety of applications. · Features new methods of audio watermarking for copyright protection and ownership protection · Outlines techniques that provide superior performance in terms of imperceptibility, robustness, and data payload · Includes applications such as data authentication, data indexing, broadcast monitoring, fingerprinting, etc. | ||
| 650 | 0 | |a Signal processing. | |
| 650 | 0 | |a Computational linguistics. | |
| 650 | 0 | |a Cryptography. | |
| 650 | 0 | |a Data encryption (Computer science). | |
| 650 | 1 | 4 | |a Signal, Speech and Image Processing . |
| 650 | 2 | 4 | |a Computational Linguistics. |
| 650 | 2 | 4 | |a Cryptology. |
| 700 | 1 | |a Shimamura, Tetsuya. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319148014 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319147994 |
| 830 | 0 | |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |x 2191-7388 | |
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| 912 | |a ZDB-2-SXE | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||