Reversible Audio Data Hiding Based on Variable Error-Expansion of Linear Prediction for Segmental Audio and G.711 Speech

Nishimura, Akira

doi:10.1587/transinf.2015mup0009

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…The work in [40] proposed a blind audio watermarking algorithm by discrete wavelet transform, which has a capacity of around 100 bps when SNR = 21 [dB], and the work in [41] proposed a robust audio watermarking scheme based on fractional Charlier moment transform, achieving SNR = 32 [dB], with capacity around 500 bps. As a popular criterion, MOS-LQO scores are used in [42], which refers to a reversible watermarking method based on variable error expansion of linear prediction applied to G711 µ-law-coded speech signals. The MOS-LQO is 4.13 for a capacity of 711 bps, 3.44 for 1253 bps, and 2.84 for 1995 bps.…”

Section: Comparison Of Different Frame Lengths and Embedding Capacitymentioning

confidence: 99%

Imperceptible and Reversible Acoustic Watermarking Based on Modified Integer Discrete Cosine Transform Coefficient Expansion

Huang,

Ito

2024

Applied Sciences

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This paper aims to explore an alternative reversible digital watermarking solution to guarantee the integrity of and detect tampering with data of probative importance. Since the payload for verification is embedded in the contents, algorithms for reversible embedding and extraction, imperceptibility, payload capacity, and computational time are issues to evaluate. Thus, we propose a reversible and imperceptible audio information-hiding algorithm based on modified integer discrete cosine transform (intDCT) coefficient expansion. In this work, the original signal is segmented into fixed-length frames, and then intDCT is applied to each frame to transform signals from the time domain into integer DCT coefficients. Expansion is applied to DCT coefficients at a higher frequency to reserve hiding capacity. Objective evaluation of speech quality is conducted using listening quality objective mean opinion (MOS-LQO) and the segmental signal-to-noise ratio (segSNR). The audio quality of different frame lengths and capacities is evaluated. Averages of 4.41 for MOS-LQO and 23.314 [dB] for segSNR for 112 ITU-T test signals were obtained with a capacity of 8000 bps, which assured imperceptibility with the sufficient capacity of the proposed method. This shows comparable audio quality to conventional work based on Linear Predictive Coding (LPC) regarding MOS-LQO. However, all segSNR scores of the proposed method have comparable or better performance in the time domain. Additionally, comparing histograms of the normalized maximum absolute value of stego data shows a lower possibility of overflow than the LPC method. A computational cost, including hiding and transforming, is an average of 4.884 s to process a 10 s audio clip. Blind tampering detection without the original data is achieved by the proposed embedding and extraction method.

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Section: Comparison Of Different Frame Lengths and Embedding Capacitymentioning

confidence: 99%

Imperceptible and Reversible Acoustic Watermarking Based on Modified Integer Discrete Cosine Transform Coefficient Expansion

Huang,

Ito

2024

Applied Sciences

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“…[12,13]. Additionally, RDH methods are applied not only to images, but also to video signals [14,15] and sound signals [16,17]. A comprehensive review of the literature on RDH methods from 1997-2016 is presented in [3].…”

Section: Related Workmentioning

confidence: 99%

Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code

Dzwonkowski

Rykaczewski

2021

IEEE Access

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In this paper, a novel reversible data hiding method for encrypted images (RDHEI) is proposed. An efficient coding scheme based on cyclic binary Golay (23, 12) code is designed to embed additional data into the least significant bits (LSBs) of the encrypted image. The most significant bits (MSBs) are used to ensure the reversibility of the embedding process. The proposed scheme is lossless, and based on the receiver's privileges, allows recovery of marked data, original data and embedded data. Furthermore, the scheme can be used with any type of data, however it is best suited to 16-bit DICOM images of monochrome photometric interpretation. A modification to the standard DICOM network model was also introduced, to point out an example application of the proposed RDHEI method, i.e. an anonymized data storage outsourcing. A computer-based analysis has been carried out and simulation results are shown at the end of this paper.

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“…For example, due to the popularity over social networks and the ease of handling, digital imagery is still one of the most popular sources for RDH. Other cover sources such as video sequences [21], speech signals [22] and texts [23] are also of increasing interest to researchers recently due to the fast development of multimedia technologies and social networking services. From the viewpoint of the data embedding mechanism, most advanced RDH algorithms use the so-called prediction errors (PEs) of the elements in the cover to be embedded to realize RDH.…”

Section: Introductionmentioning

confidence: 99%

Efficient Reversible Data Hiding Based on Connected Component Construction and Prediction Error Adjustment

et al. 2022

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To achieve a good trade-off between the data-embedding payload and the data-embedding distortion, mainstream reversible data hiding (RDH) algorithms perform data embedding on a well-built prediction error histogram. This requires us to design a good predictor to determine the prediction errors of cover elements and find a good strategy to construct an ordered prediction error sequence to be embedded. However, many existing RDH algorithms use a fixed predictor throughout the prediction process, which does not take into account the statistical characteristics of local context. Moreover, during the construction of the prediction error sequence, these algorithms ignore the fact that adjacent cover elements may have the identical priority of data embedding. As a result, there is still room for improving the payload-distortion performance. Motivated by this insight, in this article, we propose a new content prediction and selection strategy for efficient RDH in digital images to provide better payload-distortion performance. The core idea is to construct multiple connected components for a given cover image so that the prediction errors of the cover pixels within a connected component are close to each other. Accordingly, the most suitable connected components can be preferentially used for data embedding. Moreover, the prediction errors of the cover pixels are adaptively adjusted according to their local context, allowing a relatively sharp prediction error histogram to be constructed. Experimental results validate that the proposed method is significantly superior to some advanced works regarding payload-distortion performance, demonstrating the practicality of our method.

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Reversible Audio Data Hiding Based on Variable Error-Expansion of Linear Prediction for Segmental Audio and G.711 Speech

Cited by 7 publications

References 10 publications

Imperceptible and Reversible Acoustic Watermarking Based on Modified Integer Discrete Cosine Transform Coefficient Expansion

Imperceptible and Reversible Acoustic Watermarking Based on Modified Integer Discrete Cosine Transform Coefficient Expansion

Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code

Efficient Reversible Data Hiding Based on Connected Component Construction and Prediction Error Adjustment

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