Journal ArticleDOI
Localized & self adaptive audio watermarking algorithm in the wavelet domain
Arashdeep Kaur,Malay Kishore Dutta,K. M. Soni,Nidhi Taneja +3 more
- Vol. 33, pp 1-15
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TLDR
Experimental results validate that the proposed adaptive watermarking algorithm provide good imperceptibility with good robustness against signal processing attacks at adjustable payload for different types of audio signals.Abstract:
This paper presents an adaptive audio watermarking algorithm in the wavelet domain to optimize the payload under the perceptual transparency constraints of audio signal by strategically using some of its local features. Unlike existing algorithms, the watermark payload in this approach is made adaptive based on the nature of the audio signal. This localized feature based approach to determine the payload addresses the issue of over-loading and under-loading the audio signals with watermark data making the payload optimized for each individual audio host signal. Some audio features are strategically extracted and the most discriminatory features are selected using Principal Component analysis (PCA) approach. A mathematical model is designed using selected audio features like energy, zero cross mean and short time energy to evaluate the degree of embedding under perceptual transparency. It is used to estimate the number of watermarking bits to be inserted for a particular audio signal which makes the approach adaptive in nature optimizing the watermarking payload. At the embedding stage, watermark is embedded in the host audio signal in the third level detailed coefficient of wavelet domain which strikes a balance between the contradicting design parameters of perceptual transparency, robustness and optimized payload. Watermark extraction in this paper is blind with good robustness to signal processing attacks. Experimental results validate that the proposed adaptive algorithm provide good imperceptibility with good robustness against signal processing attacks at adjustable payload for different types of audio signals. Comparative analysis indicates that this proposed adaptive algorithm has better performance in terms of imperceptibility and robustness in comparison to uniform watermarking algorithm.read more
Citations
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Journal ArticleDOI
High capacity, transparent and secure audio steganography model based on fractal coding and chaotic map in temporal domain
TL;DR: The HASFC model outperforms related studies by improving the hiding capacity up to 30% and maintaining the transparency of stego audio with average values of SNR at 70.4, PRD at 0.0002 and SDG at 4.7.
Journal ArticleDOI
Novel secured scheme for blind audio/speech norm-space watermarking by Arnold algorithm
TL;DR: A new scheme for blind watermarking of speech and audio signals with good tradeoff between security, capacity, imperceptibility and robustness against various signal processing attacks for both audio and speech signals is proposed.
Journal ArticleDOI
A robust digital audio watermarking scheme based on DWT and Schur decomposition
TL;DR: The proposed digital audio watermarking scheme based on a discrete wavelet transform and Schur decomposition hybrid method is inaudible and robust against common types of attacks such as Gaussian noise, re-quantization, re -sampling, low-pass filter, high- pass filter, echo, MP3 compression, and cropping.
Journal ArticleDOI
Digital audio steganography: Systematic review, classification, and analysis of the current state of the art
TL;DR: The methods can be classified into several categories based on the most prominent idea in the embedding process; hence, a new classification is proposed and provides a scope for summarizing and understanding the most followed approaches in audio steganography.
Journal ArticleDOI
The Adaptive Multi-Level Phase Coding Method in Audio Steganography
TL;DR: Adaptive Multi-level Phase Coding (AMPC) was proposed to optimize the above issues and was able to achieve a stable embedding rate of 33 Kbps at 35 dB of SNR, which is higher than the recorded embedding rates of other phase coding methods.
References
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Journal ArticleDOI
Techniques for data hiding
TL;DR: This work explores both traditional and novel techniques for addressing the data-hiding process and evaluates these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.
Proceedings ArticleDOI
Short-time energy, magnitude, zero crossing rate and autocorrelation measurement for discriminating voiced and unvoiced segments of speech signals
TL;DR: Different methods of separating voiced and unvoiced segments of a speech signals are presented, based on short time energy calculation, short time magnitude calculation, and zero crossing rate calculation and on the basis of autocorrelation of different segments of speech signals to show that the voiced segment of speech remains periodic after applying autoc orrelation function.
Journal ArticleDOI
An audio watermarking scheme using singular value decomposition and dither-modulation quantization
TL;DR: A new audio watermarking algorithm based on singular value decomposition and dither-modulation quantization is presented that is quite robust against attacks including additive white Gaussian noise, MP3 compression, resampling, low-pass filtering, requantization, cropping, echo addition and denoising.
Journal ArticleDOI
Robust audio watermarking using improved TS echo hiding
Yousof Erfani,Shadi Siahpoush +1 more
TL;DR: Results show the good results for the system robustness against the common signal processing attacks through calculating error detection rates in comparison with conventional echo hiding methods and good results were obtained for watermark inaudibility through mean opinion test (MOS) test and SNR value comparisons.