A Robust Blind Audio Watermarking Scheme Based on DCT-DWT-SVD

Rezaei, Azadeh; Khalili, Mehdi

doi:10.1007/978-981-10-8672-4_8

Cited by 4 publications

(9 citation statements)

References 9 publications

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“…The watermarking information is hidden in the DCT coefficients of the DWT coefficients, which brings robustness to the watermarking, and the visual watermark can be extracted without a reasonable amount of distortion even under various attacks. Although the presented work in this paper has similarities with those work based on DWT-DCT-SVD in [15]- [17], the watermark embedding and extraction algorithm in this paper does not need prior information so that we can realize digital blind watermarking, such as [18].…”

Section: B Related Work and Chanllengementioning

confidence: 99%

Robust Watermarking via Multidomain Transform Over Wireless Channel: Design and Experimental Validation

Chen

2022

IEEE Access

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Watermarking is a technique that provides ownership rights for shared data, and this technique can also help to transmit confidential information to realize secure communication. In this paper, we design a blind digital watermarking based on Discrete Wavelet Transform-Discrete Cosine Transform-Singular Value Decomposition (DWT-DCT-SVD) and optimize it by genetic algorithm (GA). This watermarking has both high robustness and high imperceptibility. Then we design a transmitter and receiver system based on the IEEE 802.11a and software-defined radio (SDR). We adopt several optimization methods for the system, such as ACK/HARQ mechanism, different redundant coding, frame length adaption, adaptive modulation, and so on, aiming to improve communication reliability and rate. We verify its high communication reliability and rate through actual experiments and complete the combination of digital watermarking and wireless transmission. We could build the application scenario of Image Security Wireless Communication based on Wireless Local Area Network (WLAN) protocol and SDR platform indoors or outdoors in small areas. INDEX TERMSDiscrete cosine transform, discrete wavelet transform, image communication, image forensics, singular value decomposition, wireless LAN.

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Section: B Related Work and Chanllengementioning

confidence: 99%

Robust Watermarking via Multidomain Transform Over Wireless Channel: Design and Experimental Validation

Chen

2022

IEEE Access

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“…Audio Watermarking research has been developed by several previous researchers [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Singha and Ullah propose a combination of multi-level Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) on multiple images of different sizes as a decentralized watermark [3].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The DWT technique is also applied to Audio Watermarking by the authors [3,[10][11]. For example, paper [10] proposes a hybrid watermarking algorithm for voice signal cryptography to protect the copyright of audio files. The algorithm is formed by combining three-domain transformations, DCT, DWT, and SVD, increasing the strength of resistance to audio processing attacks.…”

Section: Introductionmentioning

confidence: 99%

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High Payload Qr-Based Data Hiding Using Secured Compressed Watermark in Polar Domain

Irawati¹,

Budiman²,

Masykuroh³

et al. 2021

Frontiers in Artificial Intelligence and Applications

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Audio Watermarking is a method to insert a copyright marker on audio. This method inserts a watermark in the information form and in a way that does not damage the audio. This technique is one of the ways to solve the problem of copyright infringement. The embedded watermark has to meet the condition of not damaging the audio and must have robustness, imperceptibility, and good capacity. The data hiding technique use the combined method of Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), QR Decomposition and Reconstruction, and Cartesian-Polar Transformation (CPT) based on Quantization Index Modulation (QIM) with the secured and compressed watermark using Compressive Sampling (CS) technique. The proposed scheme is blind Audio Watermarking as it no needs for original audio in the detection process. The combination of methods overcomes multiple attacks with guaranteed quality watermarking and high capacity. Compared to the existing technique, the data hiding technique can withstand LPF attacks, Resampling, Linear speed change (LSC), and MP3 compression. This proposed technique is also secured due to the coded watermark by a particular random key using CS. Combining CS and Audio Watermarking techniques can perform well in capacity, imperceptibility, security, and attack resistance.

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“…A nice review of the SVD-based image processing techniques is presented by Sadek (2012). Other important specific applications include image watermarking schemes (Dappuri, Rao and Sikha, 2020;Meenakshi, Swaraja and Kora, 2020;Thakkar and Srivastava, 2017), signal denoising and feature enhancements (Zhao and Jia, 2017), audio watermarking (Özer, Sankur and Memon, 2005;Rezaei and Khalili, 2019), sound source localization (Grondin and Glass, 2019a,b), sound recovery techniques (Zhang et al, 2016), etc. Moreover, SVD is recently being used extensively to solve different problems in bioinformatics, which include the analysis of protein functional associations (Franceschini et al, 2016), clustering for gene expression analysis (Horn and Axel, 2003;Liang, 2007;Bustamam, Formalidin and Siswantining, 2018), protein coding region prediction (Das, Das and Nanda, 2017), etc.…”

mentioning

confidence: 99%

A New Robust Scalable Singular Value Decomposition Algorithm for Video Surveillance Background Modelling

Roy¹,

Basu²,

Ghosh³

2021

Preprint

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A basic algorithmic task in automated video surveillance is to separate background and foreground objects. Camera tampering, noisy videos, low frame rate, etc., pose difficulties in solving the problem. A general approach which classifies the tampered frames, and performs subsequent analysis on the remaining frames after discarding the tampered ones, results in loss of information. We propose a robust singular value decomposition (SVD) approach based on the density power divergence to perform background separation robustly even in the presence of tampered frames. We also provide theoretical results and perform simulations to validate the superiority of the proposed method over the few existing robust SVD methods. Finally, we indicate several other use-cases of the proposed method to show its general applicability to a large range of problems.

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A Robust Blind Audio Watermarking Scheme Based on DCT-DWT-SVD

Cited by 4 publications

References 9 publications

Robust Watermarking via Multidomain Transform Over Wireless Channel: Design and Experimental Validation

Robust Watermarking via Multidomain Transform Over Wireless Channel: Design and Experimental Validation

High Payload Qr-Based Data Hiding Using Secured Compressed Watermark in Polar Domain

A New Robust Scalable Singular Value Decomposition Algorithm for Video Surveillance Background Modelling

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