The Experts below are selected from a list of 30318 Experts worldwide ranked by ideXlab platform
Mohammad Pooyan - One of the best experts on this subject based on the ideXlab platform.
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Adaptive Digital Audio Steganography Based on Integer Wavelet Transform
Circuits Systems & Signal Processing, 2008Co-Authors: Ahmad Delforouzi, Mohammad PooyanAbstract:In this paper a novel method for digital audio steganography is presented where encrypted Covert data is embedded into the coefficients of the host audio (Cover Signal) in the integer wavelet domain. The hearing threshold is calculated in the integer domain and this threshold is employed as the embedding threshold. The inverse integer wavelet transform is applied to the modified coefficients to form a new audio sequence (stego Signal). The characteristics of this method are large payload, high audio quality and full reCovery.
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adaptive digital audio steganography based on integer wavelet transform
Intelligent Information Hiding and Multimedia Signal Processing, 2007Co-Authors: Ahmad Delforouzi, Mohammad PooyanAbstract:In this paper a novel method for digital audio steganography is presented where encrypted Covert data is embedded into the coefficients of host audio (Cover Signal) in integer wavelet domain. The hearing threshold is calculated in the integer domain and this threshold is employed as embedding threshold. The inverse integer wavelet transform is applied to the modified coefficients to form new audio sequence (stego Signal). The characteristics of this method are large pay load, high audio quality and full reCovery.
Mohammad Ali Akhaee - One of the best experts on this subject based on the ideXlab platform.
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performance improvement of spread spectrum additive data hiding over codec distorted voice channels
Signal Processing Conference (EUSIPCO) 2014 Proceedings of the 22nd European, 2014Co-Authors: M. Boloursaz, Reza Kazemi, Ferydon Behnia, Mohammad Ali AkhaeeAbstract:This paper considers the problem of Covert communication through dedicated voice channels by embedding secure data in the Cover speech Signal utilizing spread spectrum additive data hiding. The Cover speech Signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the Covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice nonstationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape parameter needed for optimum detection is either estimated from the stego or Cover Signal respectively. The simulation results also show that the proposed method achieves acceptable robustness against the lossy compression attack by different compression rates of Adaptive Multi Rate (AMR) voice codec.
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performance improvement of spread spectrum additive data hiding over codec distorted voice channels
Signal Processing Conference (EUSIPCO) 2014 Proceedings of the 22nd European, 2014Co-Authors: M. Boloursaz, Reza Kazemi, Ferydon Behnia, Mohammad Ali AkhaeeAbstract:This paper considers the problem of Covert communication through dedicated voice channels by embedding secure data in the Cover speech Signal utilizing spread spectrum additive data hiding. The Cover speech Signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the Covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice nonstationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape parameter needed for optimum detection is either estimated from the stego or Cover Signal respectively. The simulation results also show that the proposed method achieves acceptable robustness against the lossy compression attack by different compression rates of Adaptive Multi Rate (AMR) voice codec.
Ahmad Delforouzi - One of the best experts on this subject based on the ideXlab platform.
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Adaptive Digital Audio Steganography Based on Integer Wavelet Transform
Circuits Systems & Signal Processing, 2008Co-Authors: Ahmad Delforouzi, Mohammad PooyanAbstract:In this paper a novel method for digital audio steganography is presented where encrypted Covert data is embedded into the coefficients of the host audio (Cover Signal) in the integer wavelet domain. The hearing threshold is calculated in the integer domain and this threshold is employed as the embedding threshold. The inverse integer wavelet transform is applied to the modified coefficients to form a new audio sequence (stego Signal). The characteristics of this method are large payload, high audio quality and full reCovery.
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adaptive digital audio steganography based on integer wavelet transform
Intelligent Information Hiding and Multimedia Signal Processing, 2007Co-Authors: Ahmad Delforouzi, Mohammad PooyanAbstract:In this paper a novel method for digital audio steganography is presented where encrypted Covert data is embedded into the coefficients of host audio (Cover Signal) in integer wavelet domain. The hearing threshold is calculated in the integer domain and this threshold is employed as embedding threshold. The inverse integer wavelet transform is applied to the modified coefficients to form new audio sequence (stego Signal). The characteristics of this method are large pay load, high audio quality and full reCovery.
Seyed Mohammad Ahadi - One of the best experts on this subject based on the ideXlab platform.
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Logarithmic Quantization Index Modulation: A perceptually better way to embed data within a Cover Signal
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Nima Khademi Kalantari, Seyed Mohammad AhadiAbstract:In this paper, a new method for logarithmic quantization index modulation (QIM) is proposed. In this regard a logarithmic function is first applied to the host Signal. Then the transformed Signal is quantized using uniform quantization as conventional QIM to embed watermark data within. Finally using inverse transform the watermarked Signal is obtained. The watermark extraction is performed using minimum distance decoder. The optimum parameter for data embedding with minimum quantization distortion is derived. Also the probability of error is analytically calculated and verified by simulation. Furthermore data hiding using secret key is proposed and the probability of error is obtained. Simulation results show that the proposed method outperforms the conventional QIM in terms of robustness when the perceptual quality of watermarked image for both methods are similar. Moreover, simulation shows that the proposed scheme has outstanding robustness in comparison with a recent quantization based data hiding method.
M. Boloursaz - One of the best experts on this subject based on the ideXlab platform.
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performance improvement of spread spectrum additive data hiding over codec distorted voice channels
Signal Processing Conference (EUSIPCO) 2014 Proceedings of the 22nd European, 2014Co-Authors: M. Boloursaz, Reza Kazemi, Ferydon Behnia, Mohammad Ali AkhaeeAbstract:This paper considers the problem of Covert communication through dedicated voice channels by embedding secure data in the Cover speech Signal utilizing spread spectrum additive data hiding. The Cover speech Signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the Covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice nonstationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape parameter needed for optimum detection is either estimated from the stego or Cover Signal respectively. The simulation results also show that the proposed method achieves acceptable robustness against the lossy compression attack by different compression rates of Adaptive Multi Rate (AMR) voice codec.
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performance improvement of spread spectrum additive data hiding over codec distorted voice channels
Signal Processing Conference (EUSIPCO) 2014 Proceedings of the 22nd European, 2014Co-Authors: M. Boloursaz, Reza Kazemi, Ferydon Behnia, Mohammad Ali AkhaeeAbstract:This paper considers the problem of Covert communication through dedicated voice channels by embedding secure data in the Cover speech Signal utilizing spread spectrum additive data hiding. The Cover speech Signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the Covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice nonstationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape parameter needed for optimum detection is either estimated from the stego or Cover Signal respectively. The simulation results also show that the proposed method achieves acceptable robustness against the lossy compression attack by different compression rates of Adaptive Multi Rate (AMR) voice codec.
