基于稳健特征点的平稳小波域数字水印算法

doi:10.11959/j.issn.1000-436x.2019228

Abstract

Abstract:

Aiming at the challenging work to design a robust digital audio watermarking algorithm against desynchronization attacks,a new second generation digital audio watermarking in stationary wavelet transform (SWT) domain based on robust local audio feature was proposed.First,the first-order smooth gradient response of the low-pass sub-band coefficient was calculated using Gaussian filter.Then,the short-term energy was utilized to adaptively determine local feature audio segments for embedding.Finally,the watermark information was embedded into local feature audio segments with spread transform dither modulation.The experimental results show that the proposed approach has not only good transparency,but also has strong robustness against common audio processing such as MP3 compression and good robustness against the desynchronization attacks such as pitch-scale modification et al.A SWT domain audio feature point extraction method based on smooth gradient is proposed,which effectively solves the drawbacks of poor stability and uneven distribution of audio feature points,and improves the resistance of digital audio watermarks to amplitude-scale modification,pitch-scale modification,random cropping,and jittering attacks.

Key words: digital audio watermarking, desynchronization attack, feature point, smooth gradient, stationary wavelet transform

CLC Number:

TP391

Panpan NIU,Siyu YANG,Li WANG,Hongying YANG,Li LI,Xiangyang WANG. Digital watermarking algorithm in SWT domain based on robust local feature[J]. Journal on Communications, 2019, 40(11): 187-198.

Figures/Tables 10

攻击方式	本文算法	文献[20]算法	攻击方式	本文算法	文献[20]算法
低通滤波（8 kHz）	$\frac{13}{13} (100%)$	$\frac{10}{15} (66.7 %)$	幅度伸缩（+20%）	$\frac{9}{13} (69.2 %)$	$\frac{5}{15} (33.3 %)$
低通滤波（4 kHz）	$\frac{13}{13} (100%)$	$\frac{7}{13} (53.8 %)$	幅度伸缩（+10%）	$\frac{7}{13} (53.8 %)$	$\frac{7}{15} (46.7 %)$
MP3压缩（64 kbit/s）	$\frac{10}{13} (76.9 %)$	$\frac{11}{15} (73.3 %)$	幅度伸缩（-10%）	$\frac{9}{13} (69.2 %)$	$\frac{8}{15} (53.3 %)$
MP3压缩（32 kbit/s）	$\frac{4}{13} (30.8 %)$	$\frac{8}{13} (61.5 %)$	幅度伸缩（-20%）	$\frac{12}{13} (92.3 %)$	$\frac{7}{15} (46.7 %)$
重采样（44.1-11.025-44.1 kHz）	$\frac{13}{13} (100 %)$	$\frac{10}{13} (76.9 %)$	音调变化（+5%）	$\frac{13}{13} (100 %)$	$\frac{12}{15} (80 %)$
重采样（44.1-8-44.1 kHz）	$\frac{12}{13} (92.3 %)$	$\frac{10}{15} (66.7 %)$	音调变化（-5%）	$\frac{13}{13} (100 %)$	$\frac{11}{15} (73.3 %)$
重量化（16-8-16 bit）	$\frac{13}{13} (100 %)$	$\frac{11}{15} (73.3 %)$	随机剪切（2 s）	$\frac{10}{13} (76.9 %)$	$\frac{6}{15} (40 %)$
高斯白噪声（0.01）	$\frac{13}{13} (100 %)$	$\frac{8}{13} (61.5 %)$	$抖动 (\frac{1}{5 000})$	$\frac{12}{13} (92.3 %)$	$\frac{5}{15} (33.3 %)$
添加回声（100 ms,0.5）	$\frac{9}{13} (69.2 %)$	$\frac{5}{17} (29.4 %)$	TSM（110%）	$\frac{12}{13} (92.3 %)$	$\frac{4}{15} (26.7 %)$
均衡化（baseboost）	$\frac{13}{13} (100 %)$	$\frac{5}{11} (45.5 %)$	TSM（90%）	$\frac{11}{13} (84.6 %)$	$\frac{6}{15} (40 %)$

攻击方式		本文算法			文献[19]算法
攻击方式	Danube	Heart	Piano	Danube	Heart	Piano
MP3压缩（64 kbit/s）	$\frac{12}{13} (92.3 %)$	$\frac{9}{12} (75 %)$	$\frac{10}{13} (76.9 %)$	$\frac{14}{16} (87.5 %)$	$\frac{14}{16} (87.5 %)$	$\frac{14}{16} (87.5 %)$
MP3压缩（96 kbit/s）	$\frac{12}{13} (92.3 %)$	$\frac{11}{12} (91.7 %)$	$\frac{13}{13} (100 %)$	$\frac{15}{16} (93.8 %)$	$\frac{15}{16} (93.8 %)$	$\frac{16}{16} (100 %)$
低通滤波（4 kHz）	$\frac{13}{13} (100 %)$	$\frac{11}{12} (91.7 %)$	$\frac{13}{13} (100 %)$	$\frac{14}{16} (87.5 %)$	$\frac{8}{13} (61.5 %)$	$\frac{14}{16} (87.5 %)$
低通滤波（8 kHz）	$\frac{13}{13} (100 %)$	$\frac{12}{12} (100 %)$	$\frac{13}{13} (100 %)$	$\frac{15}{16} (93.8 %)$	$\frac{15}{16} (93.8 %)$	$\frac{16}{16} (100 %)$
均衡化	$\frac{13}{13} (100 %)$	$\frac{10}{12} (83.3 %)$	$\frac{13}{13} (100 %)$	$\frac{10}{16} (62.5 %)$	$\frac{12}{16} (75%)$	$\frac{10}{16} (62.5 %)$
添加回声	$\frac{6}{13} (46.2 %)$	$\frac{6}{12} (50 %)$	$\frac{8}{13} (61.5 %)$	$\frac{14}{16} (87.5 %)$	$\frac{15}{16} (93.8 %)$	$\frac{15}{16} (93.8 %)$
消除噪声	$\frac{12}{13} (92.3 %)$	$\frac{10}{12} (83.3 %)$	$\frac{13}{13} (100 %)$	$\frac{15}{16} (93.8 %)$	$\frac{13}{16} (81 .%)$	$\frac{16}{16} (100 %)$
重新采样（44.1-16-44.1 kHz）	$\frac{13}{13} (100 %)$	$\frac{12}{12} (100 %)$	$\frac{13}{13} (100 %)$	$\frac{16}{16} (100 %)$	$\frac{14}{16} (87.5 %)$	$\frac{16}{16} (100 %)$
重新采样（44.1-22.05-44.1 kHz）	$\frac{13}{13} (100 %)$	$\frac{12}{12} (100 %)$	$\frac{13}{13} (100 %)$	$\frac{16}{16} (100 %)$	$\frac{13}{16} (81 .3%)$	$\frac{16}{16} (100 %)$

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