Audio watermarking scheme based on embedding strategy in low frequency components with a binary image

Erçelebi, Ergün; Batakçı, Leyla

doi:10.1016/j.dsp.2008.11.007

Cited by 69 publications

(36 citation statements)

References 20 publications

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“…As for our scheme, the payload, with 4 bits per frame, is $ 187 bps. This is a comparatively high capacity when compared to audio watermarking schemes described in [15,[41][42][43][44][45][46][47][48][49]51]. The payload capacity of the scheme can be improved by embedding more than 4 bits in each frame by modifying more elements in the second column of U.…”

Section: Capacitymentioning

confidence: 90%

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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: Capacitymentioning

confidence: 90%

“…According to International Federation of the Phonographic Industry (IFPI) [15,51], audio watermarking should be imperceptible when SNR is over 20 dB. SNR has been used widely to measure the quality of watermarked signal [52] which is formulated as SNR ¼ 10 log 10…”

Section: Snrmentioning

confidence: 99%

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

2011

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“…Audio watermarking schemes can be categorized in many different ways because there are many criteria [5]. Based on deployment of properties of a human auditory system, one can categorize audio watermarking into a scheme that is based on human perceptual model [6] and a scheme based solely on mathematical manipulation [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Singular-Spectrum Analysis for Digital Audio Watermarking with Automatic Parameterization and Parameter Estimation

Karnjana

Unoki

Aimmanee

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper proposes a blind, inaudible, robust digitalaudio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation.

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“…In particular, SS suffers from host rejection problem which reduces its payload capacity to increase the spreading rate, while QIM suffers from low immunity to additive noise and both have problems with MP3 compression/decompression attacks. Recently, there has been a considerable amount of work in robust watermarking of MP3 audio to overcome some of the problems of the traditional techniques [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Recent work focuses on the effects of MP3 compression/decompression sampling rate conversion, and synchronization attacks, among other attacks.…”

Section: Introductionmentioning

confidence: 99%

“…Recent work focuses on the effects of MP3 compression/decompression sampling rate conversion, and synchronization attacks, among other attacks. New watermarking techniques have emerged which combine the histogram based embedding, SVD of transform domain coefficients and the QIM are reaching promising payload values with improved robustness to different attacks [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Robust Watermarking Using Compressed Sensing Framework with Application to MP3 Audio

Fakhr¹

2012

IJMA

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Audio watermarking scheme based on embedding strategy in low frequency components with a binary image

Cited by 69 publications

References 20 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

Singular-Spectrum Analysis for Digital Audio Watermarking with Automatic Parameterization and Parameter Estimation

Robust Watermarking Using Compressed Sensing Framework with Application to MP3 Audio

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