CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-11-08
Cited: 0
Clicked: 7703
Mohammad Mosleh, Hadi Latifpour, Mohammad Kheyrandish, Mahdi Mosleh, Najmeh Hosseinpour. A robust intelligent audio watermarking scheme using support vector machine[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(12): 1320-1330.
@article{title="A robust intelligent audio watermarking scheme using support vector machine",
author="Mohammad Mosleh, Hadi Latifpour, Mohammad Kheyrandish, Mahdi Mosleh, Najmeh Hosseinpour",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="12",
pages="1320-1330",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500297"
}
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%T A robust intelligent audio watermarking scheme using support vector machine
%A Mohammad Mosleh
%A Hadi Latifpour
%A Mohammad Kheyrandish
%A Mahdi Mosleh
%A Najmeh Hosseinpour
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 12
%P 1320-1330
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500297
TY - JOUR
T1 - A robust intelligent audio watermarking scheme using support vector machine
A1 - Mohammad Mosleh
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A1 - Mahdi Mosleh
A1 - Najmeh Hosseinpour
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
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SP - 1320
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1500297
Abstract: Rapid growth in information technology and computer networks has resulted in the universal use of data transmission in the digital domain. However, the major challenge faced by digital data owners is protection of data against unauthorized copying and distribution. Digital watermark technology is starting to be considered a credible protection method to mitigate the potential challenges that undermine the efficiency of the system. Digital audio watermarking should retain the quality of the host signal in a way that remains inaudible to the human hearing system. It should be sufficiently robust to be resistant against potential attacks. One of the major deficiencies of conventional audio watermarking techniques is the use of non-intelligent decoders in which some sets of specific rules are used for watermark extraction. This paper presents a new robust intelligent audio watermarking scheme using a synergistic combination of singular value decomposition (SVD) and support vector machine (SVM). The methodology involves embedding a watermark data by modulating the singular values in the SVD transform domain. In the extraction process, an intelligent detector using SVM is suggested for extracting the watermark data. By learning the destructive effects of noise, the detector in question can effectively retrieve the watermark. Diverse experiments under various conditions have been carried out to verify the performance of the proposed scheme. Experimental results showed better imperceptibility, higher robustness, lower payload, and higher operational efficiency, for the proposed method than for conventional techniques.
In this manuscript, a novel audio watermarking technique is proposed. The introduced methodology is making use of the SVD domain to hide the watermark information and the SVMs to detect the watermark bits. The technical presentation of the manuscript is adequate, while the experimental analysis is satisfactory. The trade-off between the watermarking properties is quite noteworthy.
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