Abstract
Watermarking is a mechanism in which owner of the audio file hides the watermark information into a audio for various applications. The identity of the owner of the audio file is hidden in the audio, which is known as watermark. In this article, a quantization-based audio watermarking using singular value decomposition (SVD) is proposed. The original audio signal is converted into non overlapping two dimensional matrix blocks. The SVD is applied to each block. The watermark is embedded into audio signal by quantization of largest singular value of the block. The watermark is extracted blindly without using original audio signal. Experimental results show the watermark's high imperceptibility in the audio signal and good performance against Stirmark as well as traditional signal processing attacks. Compared with other audio watermarking methods, our method has higher embedding capacity and robust against various traditional signal processing attacks.
| Original language | English |
|---|---|
| Article number | e5253 |
| Journal | Concurrency Computation |
| DOIs | |
| Publication status | Accepted/In press - 01-01-2019 |
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All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Computer Science Applications
- Computer Networks and Communications
- Computational Theory and Mathematics
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Design of a blind quantization-based audio watermarking scheme using singular value decomposition. / Bhat K, Vivekananda; Das, Ashok Kumar; Lee, Jong Hyouk.
In: Concurrency Computation, 01.01.2019.Research output: Contribution to journal › Article
TY - JOUR
T1 - Design of a blind quantization-based audio watermarking scheme using singular value decomposition
AU - Bhat K, Vivekananda
AU - Das, Ashok Kumar
AU - Lee, Jong Hyouk
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Watermarking is a mechanism in which owner of the audio file hides the watermark information into a audio for various applications. The identity of the owner of the audio file is hidden in the audio, which is known as watermark. In this article, a quantization-based audio watermarking using singular value decomposition (SVD) is proposed. The original audio signal is converted into non overlapping two dimensional matrix blocks. The SVD is applied to each block. The watermark is embedded into audio signal by quantization of largest singular value of the block. The watermark is extracted blindly without using original audio signal. Experimental results show the watermark's high imperceptibility in the audio signal and good performance against Stirmark as well as traditional signal processing attacks. Compared with other audio watermarking methods, our method has higher embedding capacity and robust against various traditional signal processing attacks.
AB - Watermarking is a mechanism in which owner of the audio file hides the watermark information into a audio for various applications. The identity of the owner of the audio file is hidden in the audio, which is known as watermark. In this article, a quantization-based audio watermarking using singular value decomposition (SVD) is proposed. The original audio signal is converted into non overlapping two dimensional matrix blocks. The SVD is applied to each block. The watermark is embedded into audio signal by quantization of largest singular value of the block. The watermark is extracted blindly without using original audio signal. Experimental results show the watermark's high imperceptibility in the audio signal and good performance against Stirmark as well as traditional signal processing attacks. Compared with other audio watermarking methods, our method has higher embedding capacity and robust against various traditional signal processing attacks.
UR - http://www.scopus.com/inward/record.url?scp=85063913097&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063913097&partnerID=8YFLogxK
U2 - 10.1002/cpe.5253
DO - 10.1002/cpe.5253
M3 - Article
AN - SCOPUS:85063913097
JO - Concurrency Computation Practice and Experience
JF - Concurrency Computation Practice and Experience
SN - 1532-0626
M1 - e5253
ER -