A blind robust digital watermarking using invariant exponent moments

Rapid development of the digital technology and internet has made copyright protection and ownership verification of digital audio data hot research topics that have attracted a lot of interest from different parties. Since the traditional audio protection algorithms cannot solve all the problems of audio copyright protection and digital right management (DRM) due to the unique audio data features and algorithm limitations, this thesis is proposed to address the issue of audio copyright protection using watermarking techniques. Firstly, a new perception-based watermarking scheme for MPEG-4 scalable to lossless (SLS) audio is proposed. Under the control of the psychoacoustic model, the significant part of integer modified discrete cosine transform (IntMDCT) coefficients are adaptively modified during MPEG-4 SLS audio compression taking robustness, imperceptibility and security into consideration. The chaotic watermark generated by chaos is then embedded to ensure security. Moreover, the adaptive spread spectrum (SS) method is exploited to further optimize the tradeoff between robustness and transparency of this scheme. Secondly, a blind and robust audio watermarking scheme based on singular value decomposition (SVD) – followed by discrete cosine transform (DCT) with the synchronization code technique is proposed. A binary watermark is embedded into the high frequency band of the SVD-DCT block. Chaotic sequence is adopted as the synchronization code and inserted into the host signal. Thirdly, a new and robust audio watermarking scheme based on lifting wavelet transform (LWT) and SVD is proposed. Specifically, the watermark data is efficiently inserted in the low coefficient of the frequency subband of LWT audio taking advantage of both SVD and quantization index modulation (QIM). Furthermore, the synchronization code technique is also integrated in the hybrid LWT-SVD audio watermarking method. Finally, a particle swarm optimization (PSO) and SVD based audio watermarking scheme is proposed. The watermark is embedded by modifying singular values (SVs) of the host audio signal with the SS method. The designed optimization technique employs PSO to search for the optimal watermark strength by continuously adjusting the fitness values so that the conflicting requirements of robustness and imperceptibility of the watermark are satisfied optimally. Moreover, the proposed scheme has the flexibility to include or remove various watermarking attacks during training for optimization. The experimental results validate the practicality of the proposed methods and show that the proposed algorithms are very robust to typical signal manipulations. Furthermore, the results of comparison with other similar state-of-the-art audio watermarking techniques indicate that the proposed algorithms are more robust against most common signal processing attacks while preserving good imperceptibility.

An audio watermarking scheme in wavelet domain which takes advantage of substitution is proposed in this paper. First the host audio is decomposed by wavelet transform, and then convert low frequency coefficients to segments. Finally embed the watermark XOR with a pseudo-random sequence into the host audio by substitution of the segments. The experimental results illustrate that the suggested scheme has achieved high imperceptibility and is robust against common audio signal processing such as addictive noise, low-pass filtering, median filtering, re-quantifying and re-sampling.Keywordsaudio watermarkingwavelet transformpseudo-random sequencesubstitution

Digital watermarking consists in embedding imperceptible information into a host signal. It has been proposed to solve problems as varied as the protection of the copyright, content authentication, fingerprinting and broadcast monitoring. This paper presents a new approach for audio watermarking using the QR factorization in wavelet domain. This approach is based on embedding a watermark binary image in the R matrices of low frequency blocks DWT coefficients of audio signal. In this algorithm, the watermark is embedded by applying a Quantization Index Modulation (QIM) process on the determined optimal sample for each matrix R. The watermark can be blindly extracted without the knowledge of the original audio signal. Experimental results show that the proposed audio watermarking scheme maintains high quality of the audio signal. Signal to Noise Ratio (SNR), Log Spectral Distortion (LSD) and Mean Opinion Score (MOS) are about 40 dB, 0.37 dB and 4.84, respectively. Moreover, the scheme is quite robust against common signal processing attacks such as noise addition, filtering and MP3 compression. In addition, this method ensures a secure extraction process by using a private key, making it suitable for secure applications such as copyright protection.

This paper presents an audio watermarking scheme that ensures the efficient of robustness-distortion ratio and a pleasing amount of capacity. Quantization Index Modulation (QIM) method synergism along with Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and Cartesian to Polar Transformation (CPT) to emphasize copyright protection for harmonical work of art. DWT synergism along with DCT, SVD, and CPT to emphasize copyright protection for harmonical work of art. The system establishes with DWT that divides the signal within a specific range of frequency, alter it to the frequency domain by DCT, partite with mathematical processing SVD, and transform the peculiar value of matrix-S to polar value using CPT, furthermore, QIM embed the watermark into the angular value from the CPT. The system performance is astonishing, tested using 4 different audio host signal and evaluated considers to desirable Bit Error Rate (BER) <; 0.025, Signal-to-Noise Ratio (SNR)>21dB, a great amount of data payload that is 525 bit per second, and the noise caused by watermark is inaudible. All of the experiments, trials, and results show that the designed audio watermarking system is robust and imperceptible.

In this paper we propose a novel method for audio watermarking which is appropriate for real-time applications. Here the energy proportion of two successive low-middle frequency bands of each audio signal frame is computed and through the use of Index Modulation technique we embed the watermark bits into these proportion values. Low complexity is the most important characteristic of the proposed method making it appropriate for real-time applications. The method is a blind one, that is it does not need the original signal for extracting watermark bits. Experimental results have shown that it has a very good robustness against common watermarking attacks such as mp3 compression, low pass filtering, resampling, requantizing and adding noise.

In this paper, robust audio watermarking algorithm based on general orthogonal domain is proposed. By binary halftone pretreatment, one-dimensional meaningful audio watermarking is pretreated to high-fidelity binary audio. The host audio is raised to 2-dimensional space and divided into multi-sections. Each appropriate section is transformed by the general orthogonal transformation matrix. A bit binary audio watermarking signal is embedded, and the host audio is reduced to onedimensional space. So the host audio with watermarking is gotten. Because of the general orthogonal matrix, the security is higher. Experiments show that the algorithm has big embedding quantity, high security, strong practicability and robustness in enduring common attacks.

A robust and blind audio watermarking algorithm based on the discrete wavelet transform(DWT)is proposed in this paper as an effective way to resist the malicious de-synchronization attacks. The algorithm embeds the watermark information into the absolute average of audio low frequency coefficients in the DWT and error- correcting coding is applied in order to lower the bit error rate of watermark in extraction. Experimental results show the performance of the method is ideal against various common signal processing attacks, especially, robustness to de-synchronization attacks.

Moments and moment invariants have become a powerful tool in image processing owing to their image description capability and invariance property. But, conventional methods are mainly introduced to deal with the binary or gray-scale images, and the only approaches for color image always have poor color image description capability. Based on Exponent moments (EMs) and quaternion, we introduced the quaternion Exponent moments (QEMs) for describing color images in this paper, which can be seen as the generalization of EMs for gray-level images. It is shown that the QEMs can be obtained from the EMs of each color channel. We derived and analyzed the rotation, scaling, and translation (RST) invariant property of QEMs. We also discussed the problem of color image retrieval using QEMs. Experimental results are provided to illustrate the efficiency of the proposed color image descriptors.

The quick development and advance in information technology and computer networks have brought a more and more attention to data transmission in digital form. The main problem of owners and producers of digital products is to defend against distribution and unauthorized copying. An efficient solution for this disturbance is using the digital watermarking techniques. The purpose of audio digital watermarking is to insert a series of hidden information into audio files, so that it can't be heard and is robust against signal processing attacks. One of the major problems of the conventional audio watermarking schemes includes the rule-based decoders which use some sets of specific rules for watermark extraction without any intelligence. In this paper, we propose a new robust intelligent audio watermarking scheme based on a collaboration of discrete wavelet transform and K-nearest neighbor (KNN) techniques. The scheme carries out the embedding of watermark data based on modifying energy levels in wavelet domain. Moreover, an intelligent KNN learning machine is trained to capture the correlation between modified frequency coefficients, in wavelet domain, and the watermark sequence. In extracting phase, the watermarked data can be effectively retrieved using the trained KNN machine. The watermarking scheme preserves data synchronization through inserting a chaotic sequence. In order to evaluate imperceptibility and robustness of the proposed watermarking scheme, several experiments under various conditions are carried out. The experimental results show a relatively better imperceptibility, higher robustness and capacity than the conventional techniques. Data embedding rate is 1600 bps.

The technique used to hide copyright information (watermark) into the digital audio signal is termed as audio watermarking. Audio watermarking is an excellent approach to provide a solution to mitigate challenges that occur from easy copying and distribution of audio files that are being downloaded or uploaded through the web. The audio watermarking algorithms proposed earlier were implemented by image or binary logo or a unique pattern as watermark. To tackle the difficulty of online musical piracy, unethical attempt to alter purposefully copyrighted audio data and unauthorized distribution and tampering of audio files an efficient audio watermarking method is suggested here. In this method the copyright information (watermark) which is an audio signal of shorter length is imperceptibly added into the original audio signal with greater duration. Here two audio watermarking methods using DCT (Discrete Cosine Transform) and then with DWT-SVD (Discrete Wavelet Transform — singular value decomposition) methods are proposed with audio signal encrypted with secure hash algorithm as watermark. A comparative study on performance evaluation of both DCT and DWT-SVD methods are made in terms of PSNR (Peak-Signal to Noise Ratio) and MSE (Mean Square Error). The results show that transparency is best for each methods and DWT-SVD method is more efficient against signal attacks. The elementary notion of this document is to provide a beneficial and satisfactory method for secure audio file transmission by providing copyright protection.

Watermarking has attained wide consideration for copyright security of multimedia information. Audio watermarking scheme using discrete wavelet transform and singular value decomposition (SVD) along with encryption is proposed in this article. Transform domain coefficients undergo SVD and then utilizing Fibonacci numbers encrypted watermark data is inserted into the singular values to ensure achievable acquirement of watermark. Proposed algorithm utilizes chaotic and AES encrypted watermarks for embedding to accelerate the scale of security. High imperceptible attribute, robust nature and high payload are achieved using the proposed strategy. Experimental results show that the audio watermarking scheme is not only inaudible, but also robust against various common signal processing attacks such as noise addition, filtering,equantization, echo, invert and compression.

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video. However, a few algorithms have been proposed for audio watermarking. This is due to the fact that, human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). In this research work, a new method of embedding image data into the audio signal and additive audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is proposed. First, the original audio is transformed into DCT domain. The DCT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from image by image processing algorithm. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Bit Error Rate (BER) and Signal to Noise ratio (SNR) are conducted.

Audio watermarking algorithm against synchronization attacks using global characteristics and adaptive frame division

Audio watermarking has been developed to protect the copyright of audio signals. We considered the use of the distribution of the phase spectrum and propose an effective multi-bit audio watermarking method based on phase shifting. The proposed method is implemented on the basis of a frame-wise framework. The phase spectrum of each frame is first calculated, then, in accordance with the embedded bit number of each frame, the phase bins are segmented into several subsets. An artificial phase pattern is constructed in one of these subsets to carry a specific multi-bit watermark. In the water-mark extraction process, each frame is synchronized by identifying the phase pattern, then watermarks are extracted. We investigate the performance of the proposed method, and the results indicated that the proposed method balances the trade-off of inaudibility and robustness. From comparative evaluations, the proposed method also performed better than several other audio watermarking methods.

This chapter gives an overview of the digital audio watermarking systems, including description of recently developed watermarking algorithms and an overview on the existing applications that use different audio watermarking methods. Audio watermarking algorithms are characterised by six essential properties, namely: perceptual transparency,watermark bit rate, robustness, blind/informedwatermark detection, security and computational complexity. Psychoacoustic models of the HAS that are exploited in order to preserve the subjective quality of the watermarked audio during the watermarking process are shortly reviewed. The most common watermark embedding techniques ranging from the simple LSB scheme to the various spread spectrum methods are presented. Application areas that have recently been developed and possible future applications areas are listed as well.