• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.175-180
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• 2012

This paper presents a blind watermark detection scheme for an additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind source separation (BSS) based on independent component analysis (ICA) is used. Low watermark-to-signal ratio (WSR) is one of the limitations of blind detection with the additive embedding model. The proposed detector uses two-stage processing to improve the WSR at the blind detector; the first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses the resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on ICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlationbased detection schemes.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.56-59
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• 2006

A novel audio watermark design using Hilbert transform is proposed, and its superiority of performance over the existing design using the absolute values of the audio signal is demonstrated experimentally with measurements of bit error rate (BER) in correlation based decoder. (Classification No. 3.3)

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2101-2102
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• 2006

In this paper, a new digital audio watermarking algorithm is presented. The proposed algorithm embeds watermark into audio signal based on human auditory system (HAS). This algorithm is a blind audio watermarking method, which does not require any prior information during watermark extraction process. This algorithm finds watermarking position using time-domain masking effect. First we insert the watermark into wavelet domain, and then we use a back-propagation neural network (BPN) to learn the characteristics of relationship between the watermark and the watermarked audio. Due to the teaming and adaptive capabilities of the BPN, the false recovery of the watermark can be greatly reduced by the trained BPN. Experimental results show that the proposed method has good inaudibility and high robustness to common audio processing attacks.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.243-246
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• 2003

In this paper, we propose a new digital audio watermarking technique with the wavelet transform. The watermark is embedded by eliminating unnecessary information of audio signal based on human auditory system (HAS). This algorithm is an audio watermarking method, which does not require any original audio information in watermark extraction process. In this paper, the masking effect is used for audio watermarking, that is, post-tempera] masking effect. We construct the window with the synchronization signal and we extract the best frame in the window by using the zero-crossing rate (ZCR) and the energy of the audio signal. The watermark may be extracted by using the correlation of the watermark signal and the portion of the frame. Experimental results show good robustness against MPEG1-layer3 compression and other common signal processing manipulations. All the attacks are made after the D/A/D conversion.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.53-61
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• 2002

In this paper, the authors proposed the digital audio watermarking algorithm for a high quality audio. Today, the digital watermark is used to confirm to the digital copyright protection, not only the digital image but the digital audio study is an activeness in the digital watermarking area. Especially, the watermark insertion in the digital audio area affects deeply not only a robustness but the audio quality of the watermarked audio data. Generally, the audio watermark is inserted in the frequence domain after FFT, the quality of audio data is affected by the watermark insertion. Thus, a high quality audio to be maintained at the same time, the study related a inserting of the robustness watermark happened to a hot issue. In this paper, the authors proposed the digital audio watermarking algorithm using psychoacoustic model and MDCT/IMDCT (Modified Discrete Cosine Transform/Inverse Modified Discrete Cosine Transform). In the proposed scheme, the authors experimented the stereo audio file with 44.1KHz, and 128kbps for the audio watermarking algorithm proposed. When the audio data is processed by MDCT, the watermark is able to insert into the frequence domain with 256, 1024 and 2048 interval. In case of 50㎳ RMS window, it was confirmed that the difference between the original audio data and the watermarked audio data of RMS power is 0.8㏈.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.454-457
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• 2002

In this paper, we proposed digital audio watermarking algorithm for high quality audio. Nowadays, digital watermark used to confirm to digital copyright protection, not only digital image but also digital audio is active in the digital watermarking study. In this paper, we proposed digital audio watermarking algorithm using psychoacoustics model and MDCT/IMDCT (Modified Discrete Cosine Transform/Inverse Modified Discrete Cosine Transform) for the high quality audio watermark. In the proposed scheme, we used to 441KHz, 128kbps and stereo audio data for audio watermarking algorithm. Audio data is passed by MDCT; watermark can be inserted into the frequency domain with 256,1024 and 2048 interval.

• Journal of Broadcast Engineering
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• v.6 no.1
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• pp.13-20
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• 2001

In this paper, we propose a new digital audio watermarking scheme In the cepstrum domain. We insert a digital watermark signal Into the cepstral components of the audio signal using a technique analogous to spread spectrum Communications, hiding a narrow band signal in a wade band channel. In our proposed method, we use pseudo-random sequences to watermark the audio signal. The watermark Is then weighted in the cepstrum domain according to the distribution of cepstral coefficients and the frequency masking characteristics of the human auditory system. The proposed watermark embedding scheme minimizes audibility of the watermark signal. and the embedded watermark is robust to mu1tip1e watermarks, MPEG audio ceding and additive noose.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.631-635
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• 2004

The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding contents owner's audio signal in order to protect color image IPR. Since this method evolves the existing static model and embeds audio signal of big data, it has the advantage of restoring signal transformed due to attacks. Three basic stages of watermarking include: 1) Encode analogue ID owner's audio signal using PCM and create new 3D audio watermark; 2) Interleave 3D audio watermark by linear bit expansion and 3) Transform Y signal of color image into wavelet and embed interleaved audio watermark in the low frequency band on the transform domain. The results demonstrated that the audio signal embedding in color image proposed in this paper enhanced robustness against lossy JPEG compression, standard image compression and image cropping and rotation which remove a part of image.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.716-722
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• 2005

In this paper, we propose the audio watermarking algorithm based on the critical band of HAS(human auditory system) without audibly affecting the quality of the watermarked audio and implement the detecting algorithm on the BSS(broadcast synchronizing system) for testing the proposed algorithm. According to the audio quality test, the SNR(signal to noise ratio) of the watermarked audio objectively is 66dB above. In the robustness test, the proposed algorithm can detect the watermark more than $90\%$ from various compression(MP3, AAC), A/D and D/A conversions, sampling rate conversions and especially asynchronizing attacks. The BSS automatically switches the programs between the key station and the local station in broadcasting system. The result of reliability test of implemented system by using the real broadcasting audio has no false positive error during 30 days. Because of detecting once processing per 0.5 second, we can judge that the false positive error does not occur.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.125-128
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• 2000

In this paper, we proposed the high quality digital audio watermarking algorithm in the frequency domain. The spread spectrum technique is used to encrypted a stream of information by spreading the data as much of the frequency spectrum as possible. It's technique adapt well to data hiding in audio signal. We have used the perceptual model and MDCT/IMDCT for the high qualify digital audio watermarking. The proposed watermark algorithm preserved high quality audio data from watermark signal.