Blind Audio Watermarking Algorithm Research Articles

Adaptive and blind audio watermarking algorithm based on dither modulation and butterfly optimization algorithm.

How to improve the robustness to resist attacks and how to adaptively match the key parameters of the watermarking algorithm with the performance requirements to achieve the best performance in different applications are two hot issues in the research of audio watermarking algorithms. An adaptive and blind audio watermarking algorithm based on dither modulation and butterfly optimization algorithm (BOA) is proposed. Based on the convolution operation, a stable feature is designed to carry the watermark, which will improve the robustness by means of the stability of this feature to prevent the watermark loss. Blind extraction will be achieved only by comparing the feature value and the quantized value without the original audio. The BOA is used to optimize the key parameters of the algorithm which can be matched with the performance requirements by coding the population and constructing the fitness function. Experimental results confirm that this proposed algorithm can adaptively search for the optimal key parameters that match the performance requirements. Compared with other related algorithms in recent years, it exhibits strong robustness against various signal processing attacks and synchronization attacks.

Robust and Blind Audio Watermarking Algorithm in Dual Domain for Overcoming Synchronization Attacks

How to effectively resist synchronization attacks is the most challenging topic in the research of robust watermarking algorithms. A robust and blind audio watermarking algorithm for overcoming synchronization attacks is proposed in dual domain by considering time domain and transform domain. Based on analysing the characteristics of synchronization attacks, an implicit synchronization mechanism (ISM) is developed in the time domain, which can effectively track the appropriate region for embedding and extracting watermarks. The data in this region will be subjected to discrete cosine transform (DCT) and singular value decomposition (SVD) in turn to obtain the eigenvalue that can be utilized to carry watermarks. In order to extract the watermark blindly, the eigenvalue will be quantized. Genetic algorithm (GA) is utilized to optimize the quantization step to balance both transparency and robustness. The experimental results confirm that the proposed algorithm not only withstands various conventional signal processing operations but also resists malicious synchronization attacks, such as time scale modification (TSM), pitch-shifting modification (PSM), jittering, and random cropping. Especially, it can overcome TSM with strength from −30% to +30%, which is much higher than the standard of the International Federation of the Phonographic Industry (IFPI) and far superior to the other algorithms in related papers.

Adaptive and Blind Audio Watermarking Algorithm Based on Chaotic Encryption in Hybrid Domain

An adaptive and blind audio watermarking algorithm is proposed based on chaotic encryption in discrete cosine transform (DCT) and discrete wavelet transform (DWT) hybrid domain. Since human ears are not sensitive to small changes in the high-frequency components of the audio media, the encrypted watermark can be embedded into the audio signal according to the special embedding rules. The embedding depth of each audio segment is controlled by the overall average amplitude to effectively improve the robustness and imperceptibility. The watermark is encrypted by a chaotic sequence to improve the security of watermark, so only users who hold the correct key can accurately extract the watermark without the original audio signal. Experimental results show that the proposed algorithm has larger capacity, higher imperceptibility, better security, and stronger robustness when combating against signal-processing attacks than the involved audio watermarking algorithms in recent years.

Blind audio watermarking algorithm based on DCT, linear regression and standard deviation

This paper proposes a blind audio watermarking algorithm to embed data and extract them by changing the Discrete Cosine Transform (DCT) coefficients. The key idea is to divide the selected frequency band of DCT into short frames and change the samples of each frame based on the watermark bits that are embedded in. The proposed idea uses linear regression and standard deviation to extract watermark bits. The experimental results show that the method has a high capacity about 3000 bps data payload, without significant perceptual distortion. Moreover, this idea provides robustness against common signal processing attacks such as Additive White Gaussian Noise, Resampling, Re-quantizing and Echo.

Empirical mode decomposition based blind audio watermarking

Multiparty-multilevel digital rights management of audio requires blind detection of multiple watermarks. The proposed audio watermarking method offers copyright protection based on analysis filterbank decomposition, psychoacoustic model and empirical mode decomposition (EMD). The novel blind audio watermarking algorithm embeds the watermark bits in the final residue of the subbands in the transform domain. The watermarking system performance is optimized by selecting appropriate segment length for applying EMD process and by selecting the number of subbands for watermark embedding. Experimental results show that the proposed scheme is robust against various common signal processing manipulations while multiple watermark messages can be embedded.

A Robust Audio Watermarking Algorithm Based on SVD-DWT

In this paper, we proposed a novel blind audio watermarking algorithm, which combined Singular Value Decomposition(SVD) with Discrete Wavelet Transform(DWT). In our algorithm, We first partition the rearranged audio signal into blocks, then generate the vector by selecting the biggest singular values after performing SVD on these blocks. Finally we embed the watermark into the approximate components obtained from the DWT decomposition of the vector by means of quantization process. Experimental results showed that our algorithm has good robustness against the common audio signals processing operations. Compared with earlier schemes based on SVD, the proposed scheme has satisfying imperceptibility and improved payload. DOI: http://dx.doi.org/10.5755/j01.eee.20.1.3948

A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform

In this paper, combining the robustness of vector norm with that of the approximation components after the discrete wavelet transform (DWT), a blind and adaptive audio watermarking algorithm is proposed. In order to improve the robustness and imperceptibility, a binary image encrypted by Arnold transform as watermark is embedded in the vector norm of the segmented approximation components, the count of which depends on the size of the watermark image, after DWT of the original audio signal through quantization index modulation (QIM) with an adaptive quantization step selection scheme. Moreover, a detailed method has been designed to search the suitable quantization step parameters. Experimental results indicate that even though the capacity of the proposed algorithm is high, up to 102.4bps, this algorithm is still able to maintain good quality of the audio signal and tolerate a wide class of common attacks such as additive white Gaussian noise (AWGN), Gaussian Low-pass filter, Kaiser Low-pass filter, resampling, requantizing, cutting, MP3 compression and echo.

A blind audio watermarking algorithm by logarithmic quantization index modulation

In this paper we present a blind audio watermarking algorithm based on the vector norm and the logarithmic quantization index modulation (LQIM) in the wavelet domain, integrating the robustness of ...

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

This paper presents a blind audio watermarking algorithm based on the reduced singular value decomposition (RSVD). A new observation on one of the resulting unitary matrices is uncovered. The proposed scheme manipulates coefficients based on this observation in order to embed watermark bits. To preserve audio fidelity a threshold-based distortion control technique is applied and this is further supplemented by distortion suppression utilizing psychoacoustic principles. Test results on real music signals show that this watermarking scheme is in the range of imperceptibility for human hearing, is accurate and also robust against MP3 compression at various bit rates as well as other selected attacks. The data payload is comparatively high compared to existing audio watermarking schemes.

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

In this paper, we propose a new robust and blind audio watermarking algorithm based on singular value decomposition and quantization index modulation. The watermark insertion and extraction methods are based on quantization of the norm of singular values of the blocks. Audio quality evaluation tests show high imperceptibility of the watermark in the audio signal. Simulation results demonstrate that this algorithm is robust against signal-processing and stirmark attacks. The false negative error probability under the proposed scheme is close to zero. Moreover, the proposed algorithm has higher data payload and better performance than the other related audio watermarking schemes available in the literature.