Design of a blind quantization‐based audio watermarking scheme using singular value decomposition

K, Vivekananda Bhat; Das, Ashok Kumar; Lee, Jong Hyouk

doi:10.1002/cpe.5253

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…It has been widely studied as an effective solution for copyright protection [3]. Copyright information is embedded into the host audio without creating perceptible changes [4]. The copyright owner can extract copyright information from the watermarked audio file and verify the ownership of the audio.…”

Section: Introductionmentioning

confidence: 99%

Robust audio dual watermarking algorithm based on melody feature

Dou

Lan

2022

International Symposium on Artificial Intelligence and Robotics 2022

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Audio watermarking is an effective scheme for copyright protection. A robust dual watermarking scheme based on melody feature is proposed in this paper. Melody feature can be encoded for integrity verification. And then two robust watermark methods based on discrete cosine transform(DCT) and histogram are adopted to embed the watermark into the audio, which is used to resist different attacks. Tamper can be detected by comparing the melody features in the audio. In the extraction process, two groups of watermarks are extracted, and two images can be obtained. The Brenner gradient values of these two images are calculated, and the image with smaller Brenner value is selected as the final watermark image. The experimental results show that the proposed watermarking scheme has robustness to common signal processing and synchronization attacks. The robustness of the proposed watermark is better than existing algorithms.

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Section: Introductionmentioning

confidence: 99%

Robust audio dual watermarking algorithm based on melody feature

Dou

Lan

2022

International Symposium on Artificial Intelligence and Robotics 2022

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“…BW has a different procedure compared to non‐blind video watermarking (NBW) 4 and fragile image watermarking 5 methods, which is that NBW is mainly used for point‐to‐point communication between trusting parties, whereas BW is used for one‐to‐many‐points communication. NBW schemes are highly sensitive to any manipulation in host media, that is, hidden information cannot be retrieved, but the BW is more robust to media modifications and information in the multimedia, such as digital images, 6 documents, 7 audios, 8 3D models, and videos 9 . Usually, majority of existing digital image watermarking methodologies have done their examinations on binary or grayscale images using variety of algorithms such as least significant bit and discrete Fourier transform, 10 discrete cosine transform (DCT), 11 and DWT, 2,3 and so on.…”

Section: Introductionmentioning

confidence: 99%

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

Kumar¹,

Srinivas²,

Prabhakar

2021

Concurrency and Computation

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Day by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.

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“…The paper “Design of a blind quantization‐based audio watermarking scheme using singular value decomposition” by Jong‐Hyouk Lee et al 9 discusses a new audio watermarking exploiting singular value decomposition (SVD). The proposed scheme has been prototyped and compared with other similar solutions proving that it is able to have a high imperceptibility in the obtained audio signals and good performance against Stirmark as well as other traditional signal processing attacks.…”

mentioning

confidence: 99%

Novel data mining paradigms based on soft computing and machine learning in the current and upcoming information society revolution

Choi

Pop

Huang

2020

Concurrency and Computation

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The possibility of having the Internet accessibility everywhere and every time and the progressive reduction of the dimensions of hardware equipment, in addition to the advent of novel ICT paradigms realizing the Internet of Things and Smart City visions, made available the design and realization of an innovative type of applications where data play a key role, promising to achieve a non-negligible impact on the society and business processes. The right management, control, and distribution of data are extremely critical process in our society, so that it is always referred as information society. This is boosted by the proliferation of the social networks within our lives, and the upcoming of the Internet of Things within our homes and factories. Having such a vast volume of data to be processed in order to take decisions and/or infer knowledge poses a number of challenges. The issue of properly storing such data leads to the advent of different approaches than the traditional relational databases, such as the NoSQL products. The issue of supporting the scalability of the overall communication infrastructure and to balance the load of the consequent processing cause the shift from proprietary and centralized computing solutions to more distributed and multi-tenant approaches, such as the cloud computing and its variants. However, the processing is still centralized in the core of the infrastructures, and we only see a change on how such a Finally, we would like to express our sincere appreciation for the valuable contributions made by all the authors. Our special thanks go to Professor Geoffrey C. fox, the Editor in Chief of the Concurrency and Computation: Practice and Experience Journal, for allowing us to publish this Special Issue and for his great support throughout the entire publication process. 16

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Design of a blind quantization‐based audio watermarking scheme using singular value decomposition

Cited by 8 publications

References 21 publications

Robust audio dual watermarking algorithm based on melody feature

Robust audio dual watermarking algorithm based on melody feature

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

Novel data mining paradigms based on soft computing and machine learning in the current and upcoming information society revolution

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