General Regression Neural Network Based Audio Watermarking Algorithm Using Torus Automorphism
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU129591" target="_blank" >RIV/00216305:26220/18:PU129591 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TSP.2018.8441174" target="_blank" >http://dx.doi.org/10.1109/TSP.2018.8441174</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2018.8441174" target="_blank" >10.1109/TSP.2018.8441174</a>
Alternative languages
Result language
angličtina
Original language name
General Regression Neural Network Based Audio Watermarking Algorithm Using Torus Automorphism
Original language description
Accurate extraction of embedded data at the receiver end is still a major point of consideration in audio watermarking area. This paper portrays a blind audio watermarking scheme in transform domain using the combination of properties of audio signal extracted through singular value decomposition and general regression neural network leading to exact extraction of watermark. The security of embedded watermark is assured by using torus automorphism at the embedded side. Results from the experimental setup validate the accuracy of proposed scheme. The payload capacity of proposed algorithm is 62.5 bps. The comparison of proposed scheme with existing ones indicate that the proposed scheme has shown good efficiency in terms of robustness, payload and transparency.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the IEEE 2018 41st International Conference on Telecommunications and Signal Processing (TSP2018)
ISBN
978-1-5386-4695-3
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
1-4
Publisher name
IEEE
Place of publication
Athens, Greece
Event location
Athens, Greece
Event date
Jul 4, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000454845100084