基于变分贝叶斯学习的音频水印盲检测方法

doi:10.11959/j.issn.1000-436x.2015014

Abstract

Abstract:

In order to improve the performance of audio watermarking detection,a blind audio watermarking mechanism using the statistical characteristics based on MFCC features of audio frames was proposed.The spread spectrum watermarking was embedded in the DCT coefficients of audio frames.MFCC features extracted from watermarked audio frames as well as un-watermarked ones were trained to establish their Gaussian mixture models and to estimate the parameters by vatiational Bayesian learning method respectively.The watermarking was detected according to the maximum likelihood principle.The experimental results show that our method can lower the false detection rate compared with the method using EM algorithm when the audio signal was under noise and malicious attacks.Also,the experiments show that the proposed method achieves better performance in handling insufficient training data as well as getting rid of over-fitting problem.

Key words: Gaussian mixture model, audio watermarking, blind detection, over-fitting

Xin TANG,Zhao-feng MA,Xin-xin NIU,Yi-xian YANG. Blind audio watermarking mechanism based on variational Bayesian learning[J]. Journal on Communications, 2015, 36(1): 121-128.

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References 22

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攻击类型	误检率/%
攻击类型	VBEM	EM
Addbrumm 10 100	9.5	9.9
Compressor	11.4	12.8
FFT invert	4.8	6.1
Lsbzero	4.8	6.3
Normalize	4.7	6.5
Stat1	33.3	40.1
rc_highpass	5.0	6.4
Zerocross	38.2	40.1

Blind audio watermarking mechanism based on variational Bayesian learning

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