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Songbin Li - One of the best experts on this subject based on the ideXlab platform.

  • steganalysis of joint codeword Quantization Index modulation steganography based on codeword bayesian network
    Neurocomputing, 2018
    Co-Authors: Songbin Li, Jie Yang
    Abstract:

    Abstract Quantization Index Modulation Steganography (QIMS) is an important category of steganography methods for low-bit-rate compressed speech. Early QIMS utilized independent codewords for embedding. Recently, new Joint Codeword QIMS (JC-QIMS) methods have been proposed. Such methods have higher embedding efficiency and steganography security than Independent Codeword QIMS (IC-QIMS) methods. Current steganalysis methods can detect IC-QIMS effectively, but the detection accuracy for JC-QIMS is unsatisfactory, especially at low embedding rates. To improve this accuracy, a novel steganalysis method based on a newly developed Codeword Bayesian Network (CBN) is proposed. The CBN is constructed based on the probability distribution and the steganography-sensitive transition relationships of codewords. The network parameters are learned by utilizing the Dirichlet distribution as the prior distribution. Extensive experiments are conducted with multiple embedding rates, multiple speech lengths and different network complexities. The experimental results demonstrate that the proposed method outperforms the state-of-the-art QIM steganalysis method against JC-QIMS. In particular, our algorithm achieves good detection results even at relatively low embedding rates. Moreover, it is proved that our method is also effective for the steganalysis of IC-QIMS.

  • improving security of Quantization Index modulation steganography in low bit rate speech streams
    Multimedia Systems, 2014
    Co-Authors: Hui Tian, Songbin Li
    Abstract:

    In this study, we mainly concentrate on Quantization-Index-modulation (QIM) steganography in low bit-rate speech streams, and contribute to improve its security. Exploiting the characteristics of codebook division diversity in the complementary neighbor vertices algorithm, we first design a key-based codebook division strategy, which follows Kerckhoff's principle and provides a better security than the previous QIM approach. Further, to resist the state-of-the-art steganalysis, following a general belief that fewer and smaller cover changes are less detectable and more secure, we present an improved QIM steganography, which introduces random position selection to adjust the embedding rate dynamically, and employs matrix encoding strategy to enhance the embedding efficiency. The proposed approach is evaluated with ITU-T G.723.1 as the codec of cover speech and compared with the previous work. The experimental results demonstrate that the proposed approach outperforms the traditional QIM approach on both steganographic transparency and steganalysis resistance. Moreover, it is worth pointing out that our approach can effectively work in conjunction with not only G.723.1 codec but also all other parametric speech coders, and be successfully applied into Voice-over-Internet-Protocol systems.

  • detection of Quantization Index modulation steganography in g 723 1 bit stream based on Quantization Index sequence analysis
    Journal of Zhejiang University Science C, 2012
    Co-Authors: Songbin Li, Yongfeng Huang
    Abstract:

    This paper presents a method to detect the Quantization Index modulation (QIM) steganography in G.723.1 bit stream. We show that the distribution of each Quantization Index (codeword) in the Quantization Index sequence has unbalanced and correlated characteristics. We present the designs of statistical models to extract the quantitative feature vectors of these characteristics. Combining the extracted vectors with the support vector machine, we build the classifier for detecting the QIM steganography in G.723.1 bit stream. The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain. The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.

Seyed Mohammad Ahadi - One of the best experts on this subject based on the ideXlab platform.

  • A Logarithmic Quantization Index Modulation for Perceptually Better Data Hiding
    IEEE Transactions on Image Processing, 2010
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a novel arrangement for quantizer levels in the Quantization Index Modulation (QIM) method is proposed. Due to perceptual advantages of logarithmic Quantization, and in order to solve the problems of a previous logarithmic Quantization-based method, we used the compression function of ¿ -Law standard for Quantization. In this regard, the host signal is first transformed into the logarithmic domain using the ¿ -Law compression function. Then, the transformed data is quantized uniformly and the result is transformed back to the original domain using the inverse function. The scalar method is then extended to vector Quantization. For this, the magnitude of each host vector is quantized on the surface of hyperspheres which follow logarithmic radii. Optimum parameter ¿ for both scalar and vector cases is calculated according to the host signal distribution. Moreover, inclusion of a secret key in the proposed method, similar to the dither modulation in QIM, is introduced. Performance of the proposed method in both cases is analyzed and the analytical derivations are verified through extensive simulations on artificial signals. The method is also simulated on real images and its performance is compared with previous scalar and vector Quantization-based methods. Results show that this method features stronger a watermark in comparison with conventional QIM and, as a result, has better performance while it does not suffer from the drawbacks of a previously proposed logarithmic Quantization algorithm.

  • 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, 2009
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    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.

  • ICASSP - 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, 2009
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    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.

  • ICASSP - Vector Quantization Index Modulation watermarking using concentric hyperspherical codebooks
    2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a digital watermarking system based on vector Quantization is presented. Each vector containing N samples is mapped on the surface of the hyperspheres each of which are associated with a message to embed the digital watermark. We called this method vector Quantization Index modulation (VQIM) since it is conventional QIM in the N-dimensional space. The performance of the method and its comparison to orthogonal code-based watermarking is investigated. Furthermore, we implemented the VQIM method on a real audio watermarking system and adopted it with the human auditory system. The experimental results show the robustness of this scheme against common attacks in audio watermarking such as MP3 compression, lowpass filtering, resampling etc.

  • Vector Quantization Index Modulation watermarking using concentric hyperspherical codebooks
    2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a digital watermarking system based on vector Quantization is presented. Each vector containing N samples is mapped on the surface of the hyperspheres each of which are associated with a message to embed the digital watermark. We called this method vector Quantization Index modulation (VQIM) since it is conventional QIM in the N-dimensional space. The performance of the method and its comparison to orthogonal code-based watermarking is investigated. Furthermore, we implemented the VQIM method on a real audio watermarking system and adopted it with the human auditory system. The experimental results show the robustness of this scheme against common attacks in audio watermarking such as MP3 compression, lowpass filtering, resampling etc.

Bingwen Feng - One of the best experts on this subject based on the ideXlab platform.

  • IWDW - Multiple Watermarking Using Multilevel Quantization Index Modulation
    Digital Forensics and Watermarking, 2017
    Co-Authors: Bingwen Feng, Jian Weng, Wei Lu
    Abstract:

    In this paper, a type of multilevel Quantization Index Modulation (QIM) algorithms is proposed by adopting the concept of multilevel nested lattice coding. We first introduce the multilevel scalar-QIM and then extend it to the vector case by using lattice-QIM. The lattice definition and nested lattices construction are specified such that the constructed nested lattices is suitable for multilevel lattice-QIM. The proposed scheme embeds multiple watermark sequences into the same host signal via several embedding rounds. Each round of embedding uses quantizers of different radii, and thus provides different robustness. As a result, the embedded watermark sequences can be used for various purposes. Benefiting from the scalable robustness and adjustable embedding rate, the proposed multilevel QIM presents good performances and supports a wide range of applications.

  • multiple watermarking using multilevel Quantization Index modulation
    International Workshop on Digital Watermarking, 2016
    Co-Authors: Bingwen Feng, Jian Weng, Wei Lu
    Abstract:

    In this paper, a type of multilevel Quantization Index Modulation (QIM) algorithms is proposed by adopting the concept of multilevel nested lattice coding. We first introduce the multilevel scalar-QIM and then extend it to the vector case by using lattice-QIM. The lattice definition and nested lattices construction are specified such that the constructed nested lattices is suitable for multilevel lattice-QIM. The proposed scheme embeds multiple watermark sequences into the same host signal via several embedding rounds. Each round of embedding uses quantizers of different radii, and thus provides different robustness. As a result, the embedded watermark sequences can be used for various purposes. Benefiting from the scalable robustness and adjustable embedding rate, the proposed multilevel QIM presents good performances and supports a wide range of applications.

  • IWDW - Blind Watermarking Based on Adaptive Lattice Quantization Index Modulation
    Digital-Forensics and Watermarking, 2016
    Co-Authors: Bingwen Feng, Wei Lu, Zhuoqian Liang
    Abstract:

    Lattice Quantization Index Modulation (LQIM) is an important tool in blind watermarking. Traditional compensative LQIM can only handle the global tradeoff between fidelity and robustness. To adapt the embedding strength to the local perceptual characteristics of the host signal, this paper proposes an adaptive LQIM scheme. The adaptive encoder minimizes the embedding distortion in the term of weighted-mean-squared error (wMSE) while maintaining the robustness at an acceptable level. The weight value associated with each signal element can be set according to certain perceptual measurement and is not required at the decoder. Experimental results demonstrate the superiority of the proposed scheme. Compared with the compensative LQIM, the proposed adaptive LQIM provides better fidelity without the loss of robustness.

  • Robust image watermarking based on Tucker decomposition and Adaptive-Lattice Quantization Index Modulation
    Signal Processing: Image Communication, 2016
    Co-Authors: Bingwen Feng, Wei Sun, Wei Lu, Yun-qing Shi
    Abstract:

    In this paper, a robust blind image watermarking scheme with a good rate distortion-robustness tradeoff is proposed by adopting both Tucker Decomposition (TD) and Adaptive-Lattice Quantization Index Modulation (A-LQIM). Inspired by the good properties provided by TD, such as content-based representation and stable decomposition under distortions, the core tensor of TD is computed from the host image to carry watermarks. The two coarsest coefficients in each frontal slice of the core tensor are considered as a host vector, into which one watermark bit is embedded by using Lattice Quantization Index Modulation (LQIM). In order to further improve the watermarked image quality, an A-LQIM method is proposed to control the embedding strength on each host vector by approximately minimizing the Structural SIMilarity (SSIM)-measured perceptual distortion. Optimal parameters for each embedding are obtained according to the host image. Experimental results have demonstrated that the proposed scheme provides high robustness against common attacks without degrading the image quality compared with state-of-the-art schemes.

  • Blind Watermarking Based on Adaptive Lattice Quantization Index Modulation
    Digital-Forensics and Watermarking, 2016
    Co-Authors: Bingwen Feng, Zhuoqian Liang, Wei Sun, Wei Lu, Juan Liu
    Abstract:

    Lattice Quantization Index Modulation (LQIM) is an important tool in blind watermarking. Traditional compensative LQIM can only handle the global tradeoff between fidelity and robustness. To adapt the embedding strength to the local perceptual characteristics of the host signal, this paper proposes an adaptive LQIM scheme. The adaptive encoder minimizes the embedding distortion in the term of weighted-mean-squared error (wMSE) while maintaining the robustness at an acceptable level. The weight value associated with each signal element can be set according to certain perceptual measurement and is not required at the decoder. Experimental results demonstrate the superiority of the proposed scheme. Compared with the compensative LQIM, the proposed adaptive LQIM provides better fidelity without the loss of robustness.

Nima Khademi Kalantari - One of the best experts on this subject based on the ideXlab platform.

  • A Logarithmic Quantization Index Modulation for Perceptually Better Data Hiding
    IEEE Transactions on Image Processing, 2010
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a novel arrangement for quantizer levels in the Quantization Index Modulation (QIM) method is proposed. Due to perceptual advantages of logarithmic Quantization, and in order to solve the problems of a previous logarithmic Quantization-based method, we used the compression function of ¿ -Law standard for Quantization. In this regard, the host signal is first transformed into the logarithmic domain using the ¿ -Law compression function. Then, the transformed data is quantized uniformly and the result is transformed back to the original domain using the inverse function. The scalar method is then extended to vector Quantization. For this, the magnitude of each host vector is quantized on the surface of hyperspheres which follow logarithmic radii. Optimum parameter ¿ for both scalar and vector cases is calculated according to the host signal distribution. Moreover, inclusion of a secret key in the proposed method, similar to the dither modulation in QIM, is introduced. Performance of the proposed method in both cases is analyzed and the analytical derivations are verified through extensive simulations on artificial signals. The method is also simulated on real images and its performance is compared with previous scalar and vector Quantization-based methods. Results show that this method features stronger a watermark in comparison with conventional QIM and, as a result, has better performance while it does not suffer from the drawbacks of a previously proposed logarithmic Quantization algorithm.

  • 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, 2009
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    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.

  • ICASSP - 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, 2009
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    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.

  • ICASSP - Vector Quantization Index Modulation watermarking using concentric hyperspherical codebooks
    2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a digital watermarking system based on vector Quantization is presented. Each vector containing N samples is mapped on the surface of the hyperspheres each of which are associated with a message to embed the digital watermark. We called this method vector Quantization Index modulation (VQIM) since it is conventional QIM in the N-dimensional space. The performance of the method and its comparison to orthogonal code-based watermarking is investigated. Furthermore, we implemented the VQIM method on a real audio watermarking system and adopted it with the human auditory system. The experimental results show the robustness of this scheme against common attacks in audio watermarking such as MP3 compression, lowpass filtering, resampling etc.

  • Vector Quantization Index Modulation watermarking using concentric hyperspherical codebooks
    2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008
    Co-Authors: Nima Khademi Kalantari, Seyed Mohammad Ahadi
    Abstract:

    In this paper, a digital watermarking system based on vector Quantization is presented. Each vector containing N samples is mapped on the surface of the hyperspheres each of which are associated with a message to embed the digital watermark. We called this method vector Quantization Index modulation (VQIM) since it is conventional QIM in the N-dimensional space. The performance of the method and its comparison to orthogonal code-based watermarking is investigated. Furthermore, we implemented the VQIM method on a real audio watermarking system and adopted it with the human auditory system. The experimental results show the robustness of this scheme against common attacks in audio watermarking such as MP3 compression, lowpass filtering, resampling etc.

Wei Lu - One of the best experts on this subject based on the ideXlab platform.

  • IWDW - Multiple Watermarking Using Multilevel Quantization Index Modulation
    Digital Forensics and Watermarking, 2017
    Co-Authors: Bingwen Feng, Jian Weng, Wei Lu
    Abstract:

    In this paper, a type of multilevel Quantization Index Modulation (QIM) algorithms is proposed by adopting the concept of multilevel nested lattice coding. We first introduce the multilevel scalar-QIM and then extend it to the vector case by using lattice-QIM. The lattice definition and nested lattices construction are specified such that the constructed nested lattices is suitable for multilevel lattice-QIM. The proposed scheme embeds multiple watermark sequences into the same host signal via several embedding rounds. Each round of embedding uses quantizers of different radii, and thus provides different robustness. As a result, the embedded watermark sequences can be used for various purposes. Benefiting from the scalable robustness and adjustable embedding rate, the proposed multilevel QIM presents good performances and supports a wide range of applications.

  • multiple watermarking using multilevel Quantization Index modulation
    International Workshop on Digital Watermarking, 2016
    Co-Authors: Bingwen Feng, Jian Weng, Wei Lu
    Abstract:

    In this paper, a type of multilevel Quantization Index Modulation (QIM) algorithms is proposed by adopting the concept of multilevel nested lattice coding. We first introduce the multilevel scalar-QIM and then extend it to the vector case by using lattice-QIM. The lattice definition and nested lattices construction are specified such that the constructed nested lattices is suitable for multilevel lattice-QIM. The proposed scheme embeds multiple watermark sequences into the same host signal via several embedding rounds. Each round of embedding uses quantizers of different radii, and thus provides different robustness. As a result, the embedded watermark sequences can be used for various purposes. Benefiting from the scalable robustness and adjustable embedding rate, the proposed multilevel QIM presents good performances and supports a wide range of applications.

  • IWDW - Blind Watermarking Based on Adaptive Lattice Quantization Index Modulation
    Digital-Forensics and Watermarking, 2016
    Co-Authors: Bingwen Feng, Wei Lu, Zhuoqian Liang
    Abstract:

    Lattice Quantization Index Modulation (LQIM) is an important tool in blind watermarking. Traditional compensative LQIM can only handle the global tradeoff between fidelity and robustness. To adapt the embedding strength to the local perceptual characteristics of the host signal, this paper proposes an adaptive LQIM scheme. The adaptive encoder minimizes the embedding distortion in the term of weighted-mean-squared error (wMSE) while maintaining the robustness at an acceptable level. The weight value associated with each signal element can be set according to certain perceptual measurement and is not required at the decoder. Experimental results demonstrate the superiority of the proposed scheme. Compared with the compensative LQIM, the proposed adaptive LQIM provides better fidelity without the loss of robustness.

  • Robust image watermarking based on Tucker decomposition and Adaptive-Lattice Quantization Index Modulation
    Signal Processing: Image Communication, 2016
    Co-Authors: Bingwen Feng, Wei Sun, Wei Lu, Yun-qing Shi
    Abstract:

    In this paper, a robust blind image watermarking scheme with a good rate distortion-robustness tradeoff is proposed by adopting both Tucker Decomposition (TD) and Adaptive-Lattice Quantization Index Modulation (A-LQIM). Inspired by the good properties provided by TD, such as content-based representation and stable decomposition under distortions, the core tensor of TD is computed from the host image to carry watermarks. The two coarsest coefficients in each frontal slice of the core tensor are considered as a host vector, into which one watermark bit is embedded by using Lattice Quantization Index Modulation (LQIM). In order to further improve the watermarked image quality, an A-LQIM method is proposed to control the embedding strength on each host vector by approximately minimizing the Structural SIMilarity (SSIM)-measured perceptual distortion. Optimal parameters for each embedding are obtained according to the host image. Experimental results have demonstrated that the proposed scheme provides high robustness against common attacks without degrading the image quality compared with state-of-the-art schemes.

  • Blind Watermarking Based on Adaptive Lattice Quantization Index Modulation
    Digital-Forensics and Watermarking, 2016
    Co-Authors: Bingwen Feng, Zhuoqian Liang, Wei Sun, Wei Lu, Juan Liu
    Abstract:

    Lattice Quantization Index Modulation (LQIM) is an important tool in blind watermarking. Traditional compensative LQIM can only handle the global tradeoff between fidelity and robustness. To adapt the embedding strength to the local perceptual characteristics of the host signal, this paper proposes an adaptive LQIM scheme. The adaptive encoder minimizes the embedding distortion in the term of weighted-mean-squared error (wMSE) while maintaining the robustness at an acceptable level. The weight value associated with each signal element can be set according to certain perceptual measurement and is not required at the decoder. Experimental results demonstrate the superiority of the proposed scheme. Compared with the compensative LQIM, the proposed adaptive LQIM provides better fidelity without the loss of robustness.

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