Multiple Scrambling and Adaptive Synchronization for Audio Watermarking

Lin, Yiqing; Abdulla, Waleed H.

doi:10.1007/978-3-540-92238-4_34

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…The results are given for SQAM files. [4]- [6], [9] use SQAM [12] files for evaluating their suggested schemes. All the schemes in this table are robust against MP3 compression with a 128 kbps bitrate.…”

Section: Resultsmentioning

confidence: 99%

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Robust High-Capacity Audio Watermarking Based on FFT Amplitude Modification

Fallahpour

Megías

2010

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper proposes a novel robust audio watermarking algorithm to embed data and extract it in a bit-exact manner based on changing the magnitudes of the FFT spectrum. The key point is selecting a frequency band for embedding based on the comparison between the original and the MP3 compressed/decompressed signal and on a suitable scaling factor. The experimental results show that the method has a very high capacity (about 5 kbps), without significant perceptual distortion (ODG about −0.25) and provides robustness against common audio signal processing such as added noise, filtering and MPEG compression (MP3). Furthermore, the proposed method has a larger capacity (number of embedded bits to number of host bits rate) than recent image data hiding methods. key words : audio watermarking, Fast Fourier Transform (FFT)

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Section: Resultsmentioning

confidence: 99%

“…In [6], [8] the FFT domain is selected to embed watermarks for making use of the translation-invariant property of the FFT coefficients to resist small distortions in the time domain. In particular, [8] shows that the FFT domain provides excellent robustness against MP3 compression.…”

Section: Introductionmentioning

confidence: 99%

Robust High-Capacity Audio Watermarking Based on FFT Amplitude Modification

Fallahpour

Megías

2010

IEICE Trans. Inf. & Syst.

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“…Digital audio copyright scheme demonstrated in [6] embodies a psycho-acoustic model of MPEG audio coding to ensure the quality of the original sound. The algorithm presented in paper [7] proposes the use of adaptive quantization to overcome the synchronization attacks on digital audio watermarking. Such technique falls under the blind watermarking scheme.…”

Section: Related Workmentioning

confidence: 99%

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

Remya¹,

Sreekumar²,

Supriya³

et al. 2014

IJCNIS

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Guaranteeing the ownership or copyright of digital communication is of extreme importance in this digital era. Watermarking is the technique which confirms the authenticity or integrity of communication by hiding relevant information in specified areas of the original signal such that it might render it difficult to distinguish one from the other. Thus, the digital watermark can be defined as a type of indicator secretly embedded in a noise tolerant signal such as image, audio or video data.The paper presents a voice signal authentication scheme by employing signal features towards the preparation of the watermark and by embedding it in the transform domain with the Walsh transforms. Watermark used in this technique is unique for each member participating in this communication system and makes it is very imperative in the context of signal authentication.

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“…In view of the difficulties in the real audibility tests, the human subjects are not required to undergo all the 20 watermark strengths, but at an interval of four, i.e. (j = 0, 4,8,12,16,20). It means that every listener needs to do 19 tests, each of which consists of 6 watermarked signals with different strengths.…”

Section: Subjective Listening Testsmentioning

confidence: 99%

“…All of them are in WAVE format (44.1 kHz, 16 bit, mono) with a length of 4s, and most are excerpts of EBU SQAM disc tracks [15]. Then, a well-developed robust audio watermarking scheme in [16] is used to implement the process of watermarking. During the watermarking, the extent of robustness is controlled by a factor called watermark strength, which is related to the magnitude of the embedded watermark A w .…”

Section: Audio Watermarking Schemementioning

confidence: 99%

Perceptual evaluation of audio watermarking using objective quality measures

Lin

Abdulla

2008

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

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This paper proposes objective quality measures adopted in speech processing for perceptual quality evaluation of audio watermarking. Different from using an auditory perception model that mimics human auditory system, objective quality measures are introduced as alternative approach to perceive the dissimilarities caused by audio watermarking. After embedding the watermark into a variety of audio signals from EBU database, we calculate the distance between the watermarked and host signals in terms of several welldeveloped quality measures. For correlation analysis, subjective listening tests and a commercial evaluation tool PEMO-Q are also used to grade the differences. Pearson correlation coefficients reveal that the investigated quality measures, especially Weighted Spectral Slope (WSS) measure, correspond well with reference ratings. Moreover, quality measures run much faster than PEMO-Q. The results indicate that objective quality measures can be the perceptual quality predictors for audio watermarking.

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Multiple Scrambling and Adaptive Synchronization for Audio Watermarking

Cited by 8 publications

References 14 publications

Robust High-Capacity Audio Watermarking Based on FFT Amplitude Modification

Robust High-Capacity Audio Watermarking Based on FFT Amplitude Modification

An Improved Non-Repudiate Scheme-Feature Marking Voice Signal Communication

Perceptual evaluation of audio watermarking using objective quality measures

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