Efficiently Synchronized Spread‐Spectrum Audio Watermarking with Improved Psychoacoustic Model

He, Xiao; Scordilis, Michael S.

doi:10.1155/2008/251868

Cited by 9 publications

(8 citation statements)

References 14 publications

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“…Walsh functions are used in the watermark embedding process which has zero correlation between each other. Orthogonal spreading codes can be used in synchronization because the crosscorrelation between different shifts of Walsh functions is not zero [27][28][29].…”

Section: Synchronization Codementioning

confidence: 99%

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

Remya¹,

Sreekumar²,

Supriya³

et al. 2014

IJCNIS

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Guaranteeing the ownership or copyright of digital communication is of extreme importance in this digital era. Watermarking is the technique which confirms the authenticity or integrity of communication by hiding relevant information in specified areas of the original signal such that it might render it difficult to distinguish one from the other. Thus, the digital watermark can be defined as a type of indicator secretly embedded in a noise tolerant signal such as image, audio or video data.The paper presents a voice signal authentication scheme by employing signal features towards the preparation of the watermark and by embedding it in the transform domain with the Walsh transforms. Watermark used in this technique is unique for each member participating in this communication system and makes it is very imperative in the context of signal authentication.

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Section: Synchronization Codementioning

confidence: 99%

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

Remya¹,

Sreekumar²,

Supriya³

et al. 2014

IJCNIS

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“…The performance improvements were about 20 dB in signal to noise ratio. In [8], he proposed SS audio watermarking with synchronization and improved psychoacoustic model. In his paper, Discrete Wavelet Packet Transform (DWPT) is applied to the host audio before the watermark is embedded.…”

Section: Introductionmentioning

confidence: 99%

“…7. The frequency domain signal on a half of output FFT coefficients is added by output of 3 rd step as in (8) obtaining Xw. Xw length is Ls or a half of Np.…”

mentioning

confidence: 99%

FFT-Based Data Hiding on Audio in LWT-Domain Using Spread Spectrum Technique

Budiman

Suksmono

Danudirdjo

2020

ELEKTRON ELEKTROTECH

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Audio watermarking is a process to hide digital data without being seen or heard by the sense of sight or hearing. Watermaking is applied to insert the copyright on digital media, such as an image file, an audio file or a video file. In this paper, we propose watermarking procedure to embed spread spectrum watermark into frequency domain of adaptive selected subband from host audio. Lifting Wavelet Transform (LWT) is used to decompose the host audio into several subbands, and then Fast Fourier Transform (FFT) transforms selected several subbands with lowest energy. The watermark image is converted into one-dimensional signal, then it is modulated by imperceptible pseudo-noise (PN) code with controlled gain. Next, the frequency domain of audio is added by modulated and imperceptible watermark prior to transforming it to time domain by Inverse FFT (IFFT) obtaining watermarked subbands. Finally, the watermarked subbands are combined with other unused subbands by inverse LWT (ILWT) becoming the perfect version of watermarked audio. The result of this method has good robustness against most attacks from stirmark benchmark experiments, good imperceptibility with Signal to Noise Ratio (SNR) more than 30 dB and payload 172.66 bps.

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“…Xing He and Michael S. Scordilis [10] proposed a scheme based on spread spectrum technique and works fine for DA-AD conversion of line-in jack. The quality evaluation of DA-AD processes explained by Steinebach, M.; Lang, A in [5].…”

Section: Introductionmentioning

confidence: 99%

Malicious audio source detection using audio watermarking

Garlapati¹,

Kakkirala²

2015

2015 Asia Pacific Conference on Multimedia and Broadcasting

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Audio or speech can be easily recorded and manipulated with the kind of handheld devices available today. It is important to detect and prove the authenticity of an audio source especially when it is recorded by a malicious user using a mobile phone, while the audio being played by authorized device. Detection of malicious audio source is possible by using an audio watermarking technique. This audio watermarking method must be robust against geometric distortions such as time scale modification(TSM), pitch scaling, random cropping, which are inherent when audio is played back and recorded. In this work we propose a method to find the authenticity of the source of the audio using Log Coordinate Mapping(LCM) based audio watermarking[1], which is robust to geometric distortions. The watermark bits are added in appropriate frequency bands for enabling detection of change in signal characteristics when passed through the analog channel. The empirical observations reveal that our method could robustly detect the malicious source of audio if the audio is being recorded and played back by unauthorized source.

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Efficiently Synchronized Spread‐Spectrum Audio Watermarking with Improved Psychoacoustic Model

Cited by 9 publications

References 14 publications

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

FFT-Based Data Hiding on Audio in LWT-Domain Using Spread Spectrum Technique

Malicious audio source detection using audio watermarking

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