An adaptive audio watermarking based on the singular value decomposition in the wavelet domain

K, Vivekananda Bhat; Sengupta, Indranil; Das, Abhijit

doi:10.1016/j.dsp.2010.02.006

Cited by 194 publications

(133 citation statements)

References 19 publications

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“…Therefore, alterations have to be made to the SVD based image watermarking approach before it can be applied to audio. Compared with manipulating U, there are three deficiencies of manipulating S [14,15]. The first is that the modification of the largest coefficients in S [14] would cause a greater degradation [18] and it can then be easily detected and/or destroyed as the embedding position is public.…”

Section: Introductionmentioning

confidence: 99%

“…The second group SVD based schemes are 'blind' and embedding watermark information by manipulating the coefficients in the SVD decomposed matrices, such as U or S. These schemes are based on some observations proposed in [14][15][16][17][18]. Particularly, a digital image watermarking algorithm presented in [16] is based on two observations.…”

Section: Introductionmentioning

confidence: 99%

“…Most existing SVD based watermarking techniques are applied in images [16][17][18][22][23][24][25][26][27][28][29][30][31][32][33][34]. SVD based audio watermarking techniques, also exist but fewer, some of which can be found in [14,15]. All these SVD based watermarking algorithms can be categorized into two groups.…”

Section: Introductionmentioning

confidence: 99%

“…Another particular SVD based digital image watermarking algorithm proposed in [17], is formulated on the observation that the elements in the first column of U and V can be modified without significantly impacting signal integrity, allowing them to survive common attacks including compression. In [14,15], the proposed audio watermarking algorithm is based on the observation that changing S slightly does not affect the quality of the signal much and that the singular values in S are consistent under common signal processing operations. In [18], an image watermarking algorithm based on tuning the coefficients in U was proposed.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the singular value decomposition (SVD) has been used extensively as an effective technique in digital watermarking [14][15][16][17][18][22][23][24][25][26][27][28][29][30][31][32][33][34]. Most existing SVD based watermarking techniques are applied in images [16][17][18][22][23][24][25][26][27][28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

2011

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a b s t r a c tThis paper presents a blind audio watermarking algorithm based on the reduced singular value decomposition (RSVD). A new observation on one of the resulting unitary matrices is uncovered. The proposed scheme manipulates coefficients based on this observation in order to embed watermark bits. To preserve audio fidelity a thresholdbased distortion control technique is applied and this is further supplemented by distortion suppression utilizing psychoacoustic principles. Test results on real music signals show that this watermarking scheme is in the range of imperceptibility for human hearing, is accurate and also robust against MP3 compression at various bit rates as well as other selected attacks. The data payload is comparatively high compared to existing audio watermarking schemes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

2011

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A Novel Approach Towards Audio Watermarking Using FFT and CORDIC‐Based QR Decomposition

Kumar

Singh

Prakash

et al. 2021

AI and IoT‐Based Intelligent Automation in Robotics

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Design of a blind quantization‐based audio watermarking scheme using singular value decomposition

Das

Lee

2019

Concurrency and Computation

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Summary 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.

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An adaptive audio watermarking based on the singular value decomposition in the wavelet domain

Cited by 194 publications

References 19 publications

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

A Novel Approach Towards Audio Watermarking Using FFT and CORDIC‐Based QR Decomposition

Design of a blind quantization‐based audio watermarking scheme using singular value decomposition

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