Robust and secure watermarking scheme for breath sound

Lei, Baiying; Song, Insu; Rahman, Shah Atiqur

doi:10.1016/j.jss.2013.02.022

Cited by 23 publications

(15 citation statements)

References 26 publications

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“…This study compared the performance of three wavelet transform (WT)-based speech watermarking methods, namely, DWT-SVD [4], LWT-DCT-SVD, [3] and the proposed DWT-AMM. For the sake of a fair comparison, the watermark bits were embedded in the second-level approximation subband using an identical payload capacity of 200 bps for all three methods.…”

Section: Comparison With Other Wt-based Watermarking Methodsmentioning

confidence: 99%

“…Speech is a specific form of audio signal; therefore, the techniques developed for audio watermarking are presumed to be applicable to speech watermarking. However, speech differs from typical audio signals with regard to spectral bandwidth, intensity distribution, signal continuity, and production modeling [3,4]. The techniques developed for audio watermarking are not necessarily suitable for speech watermarking [5].…”

Section: Introductionmentioning

confidence: 99%

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Effective blind speech watermarking via adaptive mean modulation and package synchronization in DWT domain

Lin

Hsu

2017

J AUDIO SPEECH MUSIC PROC.

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This paper outlines a package synchronization scheme for blind speech watermarking in the discrete wavelet transform (DWT) domain. Following two-level DWT decomposition, watermark bits and synchronization codes are embedded within selected frames in the second-level approximation and detail subbands, respectively. The embedded synchronization code is used for frame alignment and as a location indicator. Tagging voice active frames with sufficient intensity makes it possible to avoid ineffective watermarking during the silence segments commonly associated with speech utterances. We introduce a novel method referred to as adaptive mean modulation (AMM) to perform binary embedding of packaged information. The quantization steps used in mean modulation are recursively derived from previous DWT coefficients. The proposed formulation allows for the direct assignment of embedding strength. Experiment results show that the proposed DWT-AMM is able to preserve speech quality at a level comparable to that of two other DWT-based methods, which also operate at a payload capacity of 200 bits per second. DWT-AMM exhibits superior robustness in terms of bit error rates, as long as the recovery of adaptive quantization steps is secured.

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Section: Comparison With Other Wt-based Watermarking Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effective blind speech watermarking via adaptive mean modulation and package synchronization in DWT domain

Lin

Hsu

2017

J AUDIO SPEECH MUSIC PROC.

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“…In a similar pattern of other evolutionary and stochastic computation techniques, such as GA and tabu-search, PSO shares similar characteristics, but it was proven that PSO could obtain better results in a faster and cheaper way compared with GA methods. Besides, another fascinating feature of PSO is that there are fewer parameters to adjust compared with GA methods (Lei et al 2013). Due to its advantage over other global optimization techniques, a myriad of watermarking scheme is developed and implemented based on PSO in this research.…”

Section: Motivationsmentioning

confidence: 99%

Ownership protection of outsourced biomedical time series data based on optimal watermarking scheme in data mining

Pham

Tran

2017

AJIS

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In the biomedical and healthcare fields, the ownership protection of the outsourced data is becoming a challenging issue in sharing the data between data owners and data mining experts to extract hidden knowledge and patterns. Watermarking has been proved as a rightprotection mechanism that provides detectable evidence for the legal ownership of a shared dataset, without compromising its usability under a wide range of data mining for digital data in different formats such as audio, video, image, relational database, text and software. Time series biomedical data such as Electroencephalography (EEG) or Electrocardiography (ECG) is valuable and costly in healthcare, which need to have owner protection when sharing or transmission in data mining application. However, this issue related to kind of data has only been investigated in little previous research as its characteristics and requirements. This paper proposes an optimized watermarking scheme to protect ownership for biomedical and healthcare systems in data mining. To achieve the highest possible robustness without losing watermark transparency, Particle Swarm Optimization (PSO) technique is used to optimize quantization steps to find a suitable one. Experimental results on EEG data show that the proposed scheme provides good imperceptibility and more robust against various signal processing techniques and common attacks such as noise addition, low-pass filtering, and resampling.

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“…Generally, watermarking scheme needs to meet the conflicting requirements of robustness, imperceptibility, capacity and security. To achieve the balance of these constraints, artificial intelligence-based approaches such as particle swarm optimization (PSO), differential evolution (DE), and genetic algorithm have been widely applied in the recent years with demonstrated remarkable performance for watermarking application [2][3][4][5][6]. An objective function is designed to achieve the balance by searching the optimal parameters.…”

Section: Introductionmentioning

confidence: 99%

“…In the recent year, the popular transform domain watermarking methods include discrete Fourier transform (DFT), discrete cosine transform (DCT), wavelet based on lifting, integer, complex transform and the derivatives of these transforms [3][4][5][6]12,13]. There are some other wavelet transforms, such as local fractional continuous and discrete wavelet transforms, [14,15] to deal with or not deal with the non-differentiable signals defined on Cantor sets, but most wavelet transforms have no local phase.…”

Section: Introductionmentioning

confidence: 99%

Optimal image watermarking scheme based on chaotic map and quaternion wavelet transform

Lei

Chen

et al. 2014

Nonlinear Dyn

Self Cite

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In this paper, an intelligent watermarking scheme optimized by adaptive differential evolution (ADE) is proposed based on chaotic map and quaternion wavelet transform (QWT). Watermark is first scrambled by a piecewise linear chaotic map to increase security and then inserted into the real QWT amplitude coefficients intelligently. ADE algorithm is explored to optimize the watermarking parameter (i.e., scaling factors) automatically. The experimental results demonstrate the high robustness against common signal processing operations, especially geometrical distortions of the proposed algorithm. Comparison results also indicate the superiority of the proposed algorithm over the existing watermarking algorithm.

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Robust and secure watermarking scheme for breath sound

Cited by 23 publications

References 26 publications

Effective blind speech watermarking via adaptive mean modulation and package synchronization in DWT domain

Effective blind speech watermarking via adaptive mean modulation and package synchronization in DWT domain

Ownership protection of outsourced biomedical time series data based on optimal watermarking scheme in data mining

Optimal image watermarking scheme based on chaotic map and quaternion wavelet transform

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