The objective of developing a robust watermarking technique is to incorporate the maximum possible robustness without compromising with the transparency. Multiple scaling factors are used to embed the watermark image into the host by multiplying these scaling factors with the Singular Values SV of the host audio. Firefly Algorithm is used to optimise the modified host audio to achieve the highest possible robustness and transparency.
Aiming at content-based audio retrieval CBAR applications, a robust audio hashing scheme is proposed. First the audio is divided to frame by fixed length and then low-frequent and high-frequent components are obtained by three-level lifting-based wavelet transformation in every frame.
Secondly the audio frame is approximately represented as a product of a base matrix and an encoding matrix, or coefficient matrix, using non-negative matrix factorization NMF. Finally the sum of each column in the coefficient matrix is calculated, which is then quantized to produce one bit Audio watermarking ieee paper the hash sequence.
Experiment results show that the proposed scheme is robust against Mp3 compression, Real compression, filtering, amplitude compression, equalization, echo, etc.
It is insensitive to small local change, and therefore is suitable for distinguishing different audios. This paper proposed an audio watermark algorithm with synchronization in wavelet domain based on support vector machine. The synchronization code and encrypted digital watermark are embedded into the low frequency coefficients in DWT domain by using quantization modulation, the image watermark and the synchronization code are extracted through SVM possessing two-class problem.
The experimental results show that the audio watermarking scheme is inaudible, but also robust against noise adding, filtering, random cropping attacks.
This thesis proposes a new algorithm of the Chaos-based audio data hiding. The Chaos theory is introduced in design a new algorithm of the audio data hiding: Experimental results show that embedded watermark is imperceptibility and robust to many attacks, such as noise adding, re-sampling, low pass filtering, reverberation, MP3 compression and re-quantization and so on.
The process of hiding the information like text, binary image, audio etc. The approach involved in watermarking the binary image signal in the wavelet domain of the audio signal was implemented using MATLAB.
In this paper, we propose a Discrete Wavelet Transform low frequency to high frequency. Besides, the high frequency spectrum is less sensitive to human ear. That is the reason why the high frequency component is usually discarded in the compression process.
Therefore, information to be hidden can be embedded into the low frequency component to against the compression attack. The characteristic of this scheme is that the user can not only use the DAW to embed the text file in to the audio but also binary image.
In this paper we embeds copyright information into audio files as a proof of their ownership, we propose an effective, robust, and an inaudible audio watermarking algorithm. The effectiveness of the algorithm has been brought by virtue of applying the discrete wavelets transform DWT.
Experimental results will be presented in this paper to demonstrate the effectiveness of the proposed algorithm. A kind of multifunctional audio digital watermark algorithm was put forward according to the copyright protection of audio problems.
The audio signal is layered three by wavelet packet decomposition and robust watermark is embedded in the low frequency part, fragile watermark is embedded in the intermediate frequency part. The experimental results show that, the algorithm has no sound very good, excellent robustness and fragility.
In the actual use of the process, which not only guarantees the safety of audio information effectivelybut also guarantees good audio information fidelity.IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL.
21, NO. 3, MARCH Audio Watermarking Via EMD Kais Khaldi and Abdel-Ouahab Boudraa, Senior Member, IEEE Abstract—In this paper a new adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD) is introduced.
This paper proposes a blind digital audio watermarking algorithm that utilizes the quantization indexmodulation (QIM) and the singular value decomposition (SVD) of stereo audio signals.
terial in this paper was presented in part at the IEEE International Symposia on Information Theory, Cambridge, MA, August , and Sorrento, Italy, June lished algorithms in current audio and image watermarking INFORMATION-THEORETIC ANALYSIS OF INFORMATION HIDING as.
(Logos, Paper Watermarks) Fragile Robust Audio torosgazete.com this case, time and frequency masking properties of the human ear are used to conceal the watermark and make it inaudible.
The greatest difficulty lies in synchroniz- Watermarking - Potentials, IEEE. author = "Shervin Shokri and Mahamod Ismail and Nasharuddin Zainal and Abdollah Shokri". A high robust approach for the additive spread spectrum audio watermarking scheme based on orthogonal decomposition of the host signal has been proposed.
A New Approach to Audio Watermarking Using Discrete Wavelet and Cosine Transforms Hooman Nikmehr, Sina Tayefeh Hashemy Abstract—Audio watermarking is a technique that hides copy- right information into the digital audio signal. This paper proposes a blind digital audio watermarking algorithm that utilizes the quantization indexmodulation (QIM) and the singular value decomposition (SVD) of stereo audio signals. This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data.