A robust audio digital watermarking algorithm based on inversed spectrum domain
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In this paper, we propose a novel robust audio watermarking scheme in spectrum. Because most of audio spectrum coefficient value are around zero except for two sides, we propose to embed data by manipulating statistical mean of selected spectrum coefficients. Our experiment results have shown that the novel audio watermarking scheme in spectrum domain can achieve imperceptibleness and robustnessKeywords:
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In this paper, we present a mean quantization based audio watermarking scheme in the wavelet transform domain. The watermark data was embedded by quantizing the means of two selected bands of the wavelet transform of the original audio signal. One of the bands was in the lower frequency and the other one in the higher frequency ranges. Adaptive step sizes were used to achieve robustness and good transparency. As a result of selecting high and low frequency bands, this scheme is robust to both high- pass and low-pass attacks. The decoder detects the watermark data without any need to the original signal. The simulation results show that this watermarking scheme performs better than many recently proposed methods regarding robustness against common attacks such as MP3 compression, adding white Gaussian noise, filtering, resampling, etc.
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The technology of embedding image into the audio signal has been researched and an algorithm of additive audio watermarking based on SNR to determine a scaling parameter /spl alpha/ is proposed. The visually recognizable binary watermark image could be embedded in the original signal wavelet domain in the algorithm. The intensity of embedded watermarks on the different audio segments would be modified by adaptively modulating the scaling parameter /spl alpha/. The experimental result demonstrate that the watermark is imperceptible and the algorithm is robust to many operations to digital audio signal, such as resampling, cropping, low pass filter, MP3 compression and so on. The algorithm is better than that without using SNR, and has a reference value to blind watermarking.
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This paper proposes a novel robust audio watermarking method based on phase coding. The quantization index modulation technique is employed for embedding watermarks into the phase spectrum of audio signals. To increase robustness of the proposed method, the region of phase spectrum that is resistant against attacks is selected for embedding. We experimentally analyzed the phase spectrum to find out which region is not distorted under attacks. On the other hand, the quantization step size is suitably selected so that the modification of phase does not cause severe distortion in sound quality. The experimental results show that the watermarks could be kept inaudible in audio signals and robust against attacks. The proposed method has the ability to embed watermarks into audio signals up to 400 bits per second with a bit error rate of less than 1%.
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This paper presents an audio watermarking scheme which is based on an efficiently synchronized spread‐spectrum technique and a new psychoacoustic model computed using the discrete wavelet packet transform. The psychoacoustic model takes advantage of the multiresolution analysis of a wavelet transform, which closely approximates the standard critical band partition. The goal of this model is to include an accurate time‐frequency analysis and to calculate both the frequency and temporal masking thresholds directly in the wavelet domain. Experimental results show that this watermarking scheme can successfully embed watermarks into digital audio without introducing audible distortion. Several common watermark attacks were applied and the results indicate that the method is very robust to those attacks.
Psychoacoustics
Distortion (music)
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Distortion (music)
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Cepstrum
Robustness
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Spread spectrum watermarking proceeds by extracting a feature vector from the cover contents and embedding a pseudo-random watermark signal in that feature vector. To detect the presence of the watermark, a correlation of the feature vector with the pseudo-random signal is performed and the result compared to a threshold. This correlation detection function is a first-order function of the feature vector components. In recent work, we have proposed that higher-order polynomial detection functions, combined with a side-informed watermark embedding strategy, can be used to increase the efficiency of the watermarking system. We have demonstrated this through a statistical analysis. In this paper, we apply our new family of detection functions to the watermarking of real audio signals. The schemes are tested on a database of over 300 different audio signals and a robustness analysis is performed on the experimental results.
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In this work, we present a novel robust audio watermarking method in wavelet domain. Embedding of watermarks is performed in a perceptually significant set of sub-bands of the host audio. In order to enhance security, watermark is embedded in a randomly selected sub-band of the host audio according to a secret key. Watermark embedding to a mapped subband is done in a predefined time period, similarly to frequency hopping approach in digital communications. Detection method is a statistical method motivated by modified patchwork algorithm, relying on large data sets. Using simple Haar decomposition and test statistics, the algorithm proved itself in the terms of computational complexity. Subjective listening test proved high perceptual transparency of the watermarked audio clips. Using embedding rate of 4.61 bps, high robustness against common audio watermarking attacks was obtained, with average bit error rate lower than 1%.
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This paper proposes an audio watermarking scheme based on singular-spectrum analysis (SSA) and differential evolution. In our framework, a watermark is embedded into an audio signal by modifying the amplitude of some oscillatory components which are decomposed by SSA, and a parameter set for the modification is determined by differential evolution. Test results showed that, although there is a trade-off between inaudibility and robustness, the sound quality of watermarked signal could be improved considerably while the bit error rate could be satisfied. Our proposed scheme is inaudible and robust. Furthermore, based on analyzing the second derivative of singular spectrum, it was found that our proposed scheme can be completely blind.
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Singular Spectrum Analysis
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In this paper, we present a novel audio watermarking scheme based on spread spectrum techniques that embeds a digital watermark within an audio signal using the instantaneous mean frequency (IMF) of the signal. Audio watermarking offers a solution to data piracy and helps to protect the rights of the artists and copyright holders. Our content-based algorithm aims to satisfy and maximize both imperceptibility and robustness of the watermark. In addition, our technique uses the short-time Fourier transform of the original audio signal to estimate a weighted IMF of the signal. Based on the masking properties of the psychoacoustic model, we then derive the required sound pressure level of the watermark. From these results, modulation is performed to produce a signal-dependent watermark that is imperceptible. The proposed method allows 25 bits to be embedded and recovered within a 5 second sample of an audio signal. Experimental results have shown that our scheme is robust to common signal processing attacks including filtering, MP3 compression and noise addition.
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SIGNAL (programming language)
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