State Transition Based Embedding in Cepstrum Domain for Audio Copyright Protection

Dhavale, Sunita Vikrant; Deodhar, Rajendra S.; Pradhan, Debasish; Patnaik, L. M.

doi:10.1080/03772063.2014.987704

Cited by 3 publications

(5 citation statements)

References 10 publications

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“…The quality of the audio signal to be restored after adding watermark. The imperceptibility is In frequency domain audio watermarking techniques, various transforms such as discrete wavelet transform (DWT), fast Fourier transform (FFT), modified discrete cosine transform (MDCT), and cepstral coefficient transforms are used, and the watermark bits are embedded in the transform coefficients [3,[14][15][16][17]. Different transforms are cascaded to increase the robustness and imperceptibility of the audio watermarking techniques.…”

Section: Imperceptibilitymentioning

confidence: 99%

Robust image-in-audio watermarking technique based on DCT-SVD transform

Kanhe¹,

Gnanasekaran²

2018

J AUDIO SPEECH MUSIC PROC.

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In this paper, a robust and highly imperceptible audio watermarking technique is presented based on discrete cosine transform (DCT) and singular value decomposition (SVD). The low-frequency components of the audio signal have been selectively embedded with watermark image data making the watermarked audio highly imperceptible and robust. The imperceptibility of proposed methods is evaluated by computing signal-to-noise ratio and by conducting subjective listening tests. The robustness of proposed technique is evaluated by computing bit error rate and average information loss in retrieved watermark image subjected to MP3 compression, AWGN, re-sampling, re-quantization, amplitude scaling, low-pass filtering, and high-pass filtering attacks with high data payload of 6 kbps. The information-theoretic approach is used to model the proposed watermarking technique as discrete memoryless channel. The Shannon's entropy concept is used to highlight the robustness of proposed technique by computing the information loss in retrieved watermarked image.

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Section: Imperceptibilitymentioning

confidence: 99%

Robust image-in-audio watermarking technique based on DCT-SVD transform

Kanhe¹,

Gnanasekaran²

2018

J AUDIO SPEECH MUSIC PROC.

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“…An 8×8 coefficient matrix D can be obtained from a DCT transformation of an audio signal s(n), as shown in Figure 3. The most robust embedding method recommended is embedding at Position (0,0), while the most transparent one is at Position (7,7). Embedding at Position (0,0) can improve robustness but adds more perceptual distortion, while embedding at Position (7,7) can improve imperceptibility but offers less robustness.…”

Section: Random Embedding Strategymentioning

confidence: 99%

“…(3) divide the audio signal equally into n segments as s (j); (4) sampling the s (j) to c (j); (5) ∀c(j), initialize j=1; (6) while! end do (7) if j≤n then (8) calculate the phase spectrum ( ) of s(j); (9) determine the position of the maxima and minima in ( ); (10) calculate the coefficient matrix C (j) by 8 × 8 DCT of c(j); (11) if the maxima is in front of the minima then (12) embedding the kv (j) at C (2,2); (13) else (14) embedding the kv (j) at C (4,4); selected as the embedding position instead. Position L or H is the Boolean choice for random embedding.…”

Section: Security and Communication Networkmentioning

confidence: 99%

“…Therefore, after embedding the I.O. on the i-th coefficient of s(n), the SNR can be calculated according to (6), (7), and (9), as shown in (13).…”

Section: Audio Quality Criterion the Signal To Noise Ratio (Snr)mentioning

confidence: 99%

“…However, currently available audio protection solutions are generally oriented towards copyright [2][3][4], and more details can be found in the survey done by R. D. Shelke et al [5]. These studies are not only in time domain [6], but also in various transform domains to discuss how to protect the integrity of audio signals [7][8][9][10]. The issue of audio integrity protection for network interaction scenarios is rarely studied.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Relative Phase Based Audio Integrity Protection Method: Model and Strategy

Lei

Zhang

et al. 2018

Security and Communication Networks

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Audio oriented integrity protection should consider the characteristics of audio signals based on the combination of audio application scenarios. However, in the current popular network interaction environment, traditional verification based solutions can no longer work. A kind of integrity protection scheme for audio business should be redesigned in these new scenarios. In this context, a method of audio integrity protection based on relative phase (RP-AIP) is proposed. Through the design of integrity object (I.O.), the integrity of audio can be abstracted as the completeness and accuracy of it. The I.O. is bound to the audio signal in a uniformly and randomly embedded manner, and the embedding rules are controlled by the relative phase characteristic of the audio itself. The model and strategy of RP-AIP are illustrated, and the corresponding process and algorithm are demonstrated as well. Simulation experiments illustrate the feasibility of the proposed solution and indicate the superiority of its performance.

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Blind Audio Watermarking Scheme Based on Improved Cepstral Statistical Mean Modulation

Zhang

Liu

2019

Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

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State Transition Based Embedding in Cepstrum Domain for Audio Copyright Protection

Cited by 3 publications

References 10 publications

Robust image-in-audio watermarking technique based on DCT-SVD transform

Robust image-in-audio watermarking technique based on DCT-SVD transform

A Relative Phase Based Audio Integrity Protection Method: Model and Strategy

Blind Audio Watermarking Scheme Based on Improved Cepstral Statistical Mean Modulation

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