An efficient and simple Audio Watermarking using DCT-SVD

Suresh, G.; Lalitha, N.V.; Rao, Ch. Srinivasa; Sailaja, V.

doi:10.1109/icdcsyst.2012.6188699

Cited by 16 publications

(11 citation statements)

References 4 publications

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“…The basic idea of DWT is to separate frequency details, which is multi-resolution decomposition [8]. The audio signal can be transformed into frequency domain ranging from low frequency to high frequency [9]. But, high frequency spectrum is less sensitive to human ear.…”

Section: Discrete Wavelet Transformmentioning

confidence: 99%

“…Fingerprinting applications (in order to distinguish distributed data). 9. In health care, especially medical imaging systems.…”

Section: Applicationmentioning

confidence: 99%

“…[9] Step 4: Apply DWT transformation on original audio signal. This operation produces two sub-bands: A and D. The D represents Details sub-band and A represents the Approximation sub-band [9]. Select the sub-band A for embedding.…”

Section: Fig 4: Watermark Embedding Processmentioning

confidence: 99%

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An Effective Audio Watermarking using DWT-SVD

Mishra¹,

Patil²,

Chitode³

2013

IJCA

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Audio watermarking has been proved as a powerful tool against illegal manipulation of audio products. It is generally used as a multimedia copyright protection tool. In this paper, we propose an audio watermarking algorithm based on two mathematical functions: Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). These algorithms performance is validated in the presence of the standard watermarking attacks. A new audio signal framing, DWT matrix formation and embedding methods are proposed and successfully implemented to improve the quality of watermarked audio. Natural variability of speech features allows watermarking alterations to be imperceptible to the human observer. On the other hand, significance of these features makes the system robust to common signal processing operations.

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Section: Discrete Wavelet Transformmentioning

confidence: 99%

“…Fingerprinting applications (in order to distinguish distributed data). 9. In health care, especially medical imaging systems.…”

Section: Applicationmentioning

confidence: 99%

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An Effective Audio Watermarking using DWT-SVD

Mishra¹,

Patil²,

Chitode³

2013

IJCA

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“…For example, the usage of some information from a watermark in an extraction process can be used as a criterion. Earlier schemes [9], [11], [13], [21] used such information. Therefore they are non-blind.…”

Section: Introductionmentioning

confidence: 99%

“…For example, some schemes [12], [14], [15], [18]- [20] modify only the largest singular value. Other schemes [7], [8], [17], [21], [22] modify all singular values, and there is a scheme [23] that modifies only some small singular values.…”

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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Secure audio signal transmission based on color image watermarking

Dandooh¹,

El‐Fishawy

El‐Samie

et al. 2021

Security and Privacy

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This paper presents a new color image watermarking system with encrypted audio signals using singular value decomposition (SVD), Arnold, and chaotic techniques for secure audio transmission over open channels. This system is based on embedding encrypted audio watermarks after transforming them into a 2-D format in the singular values of the color cover image components. Three different audio watermarks are embedded in the three color image components after separating the cover image into its red, green and blue components. The three resulting watermarked components are merged again to produce the final color watermarked image. To maintain the audio signal quality, we estimate some audio signal quality metrics after converting the audio signal into a 1-D format. The transformation from the 1-D to 2-D formats is performed through lexicographic ordering. Simulation results demonstrate that the proposed system preserves the high quality of the RGB cover image. In addition, the audio watermark extraction and decryption are possible, even in the presence of attacks. Furthermore, the results show an enhancement in the watermark detectability in the presence of severe attacks, such as rotation, blurring, cropping, histogram equalization, and noise addition to the watermarked images.

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An efficient and simple Audio Watermarking using DCT-SVD

Cited by 16 publications

References 4 publications

An Effective Audio Watermarking using DWT-SVD

An Effective Audio Watermarking using DWT-SVD

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

Secure audio signal transmission based on color image watermarking

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