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空域强鲁棒零水印方案

熊祥光

熊祥光. 空域强鲁棒零水印方案. 自动化学报, 2018, 44(1): 160-175. doi: 10.16383/j.aas.2018.c160478
引用本文: 熊祥光. 空域强鲁棒零水印方案. 自动化学报, 2018, 44(1): 160-175. doi: 10.16383/j.aas.2018.c160478
XIONG Xiang-Guang. A Zero Watermarking Scheme with Strong Robustness in Spatial Domain. ACTA AUTOMATICA SINICA, 2018, 44(1): 160-175. doi: 10.16383/j.aas.2018.c160478
Citation: XIONG Xiang-Guang. A Zero Watermarking Scheme with Strong Robustness in Spatial Domain. ACTA AUTOMATICA SINICA, 2018, 44(1): 160-175. doi: 10.16383/j.aas.2018.c160478

空域强鲁棒零水印方案

doi: 10.16383/j.aas.2018.c160478
基金项目: 

国家自然科学基金 61309006

贵州省教育厅创新群体重大研究项目 Qian-Jiao-He KY Zi [2016] 027

中央引导地方科技发展专项资金 Qian-Ke-Zhong-Yin-Di [2016]4006

贵州省教育厅自然科学基金 Qian-Jiao-He KY Zi [2015]434

详细信息
    作者简介:

    熊祥光 贵州师范大学大数据与计算机科学学院副教授.主要研究方向为多媒体信息安全和数字水印技术.E-mail:xxg0851@163.com

A Zero Watermarking Scheme with Strong Robustness in Spatial Domain

Funds: 

National Natural Science Foundation of China 61309006

Major Research Program of Creative Groups of Educational Commission of Guizhou Province Qian-Jiao-He KY Zi [2016] 027

Central Leading Local Science and Technology Development Special Foundation Qian-Ke-Zhong-Yin-Di [2016]4006

Natural Science Foundation of Educational Commission of Guizhou Province Qian-Jiao-He KY Zi [2015]434

More Information
    Author Bio:

    Associate professor at the School of Big Data and Computer Science, Guizhou Normal University. His research interest covers multimedia information security and digital watermarking technology

  • 摘要: 为了解决传统鲁棒水印技术不可感知性和鲁棒性间的矛盾,对空域零水印技术进行研究,分析了常规图像处理攻击对载体图像所有选择分块整体均值与分块均值间大小关系的影响,结果表明此关系具有较强的稳健性.基于此,提出了一种新的空域强鲁棒零水印方案.1)利用混沌系统对初值敏感的特性映射图像分块的位置和采用混沌加密与Arnold空间置乱技术对原始水印信号进行预处理;2)采用载体图像所有选择分块整体均值与分块均值间大小关系的稳健性能来构造特征信息;3)采用混沌加密和Arnold空间置乱技术对生成的零水印信号进行后处理.仿真实验结果表明,本文算法对常规的图像处理、尺寸缩放、旋转和多种组合攻击等都表现出较强的抗攻击能力.与相似的鲁棒零水印方案相比,本文算法的平均运行时间不仅减少了约90%,而且抗攻击平均性能提高了约15%,表明它具有较低的计算复杂度和更优越的鲁棒性能,适用于对载体图像质量要求较高的作品版权保护应用场合.
    1)  本文责任编委 赖剑煌
  • 图  1  所有选择分块整体均值与各个分块均值间差值关系图

    Fig.  1  The flowchart of differences relationship between the overall mean of all selected blocks and each block mean

    图  2  原始的水印和生成的零水印

    Fig.  2  Original watermarking and generated zero watermarking

    图  3  原始的测试图像

    Fig.  3  Original test image

    图  4  不同分块大小对本算法性能的影响

    Fig.  4  The effect of the algorithm performance for different block size

    图  5  不同分块大小实验结果

    Fig.  5  Experimental results with different block size

    图  6  本文算法安全性测试

    Fig.  6  Security testing of the proposed algorithm

    图  7  生成的零水印与伪随机二值信号间的相似度

    Fig.  7  Similarities between the generated zero watermarking and random binary signal

    表  1  所有选择分块整体均值与分块均值间差值关系变化情况(%)

    Table  1  The changes of difference relationship between the overall mean of all selected blocks and block mean (%)

    图像集攻击方式 $P_{1}$ $P_{2}$ $P_{3}$ $P_{4}$
    JPEG压缩(20)2.54170.850621.1772
    中值滤波(3 × 3)2.70670.720221.0870
    Kodak维纳滤波(3 × 3)2.68600.740621.033421.0992
    椒盐噪声(0.1)10.60742.753322.5952
    高斯噪声(0.1)13.56413.160722.6128
    JPEG压缩(20)3.30642.686733.8072
    中值滤波(3 × 3)3.34762.478633.8938
    SIPI维纳滤波(3 × 3)3.14662.422033.613534.2121
    椒盐噪声(0.1)12.02459.935935.5716
    高斯噪声(0.1)13.632111.831535.8746
    JPEG压缩(20)3.00590.468412.9183
    中值滤波(3 × 3)3.28480.441112.8613
    UCID维纳滤波(3 × 3)2.99850.399612.877912.9180
    椒盐噪声(0.1)13.43091.545914.1185
    高斯噪声(0.1)19.50501.799514.3138
    下载: 导出CSV

    表  2  组合攻击

    Table  2  Combination attacks

    JPEG压缩中值滤波维纳滤波椒盐噪声高斯噪声
    攻击方式1203 × 33 × 30.10.1
    攻击方式2155 × 55 × 50.20.2
    攻击方式3107 × 77 × 70.30.3
    下载: 导出CSV

    表  3  在给定阈值条件下, 所有选择分块整体均值与分块均值间差值关系变化情况(%)

    Table  3  The changes of difference relationship between the overall mean of all selected blocks and block mean with a given threshold (%)

    图像集阈值$T$攻击方式 $P_{1}$$P_{2}$ $P_{3}$$P_{4}$
    Kodak10攻击方式16.33251.641921.7064
    攻击方式212.27793.105821.033422.4345
    攻击方式322.43674.888723.4951
    20攻击方式15.42442.877539.5189
    攻击方式211.90986.141838.210041.3628
    攻击方式321.638310.018643.5223
    SIPI10攻击方式17.06205.849434.6629
    攻击方式214.605610.555933.613536.0441
    攻击方式325.864916.038438.2140
    20攻击方式14.74136.257059.5355
    攻击方式210.297912.762458.079361.7652
    攻击方式317.472820.536664.3733
    UCID10攻击方式18.55280.918113.4140
    攻击方式219.87701.994312.877914.1996
    攻击方式339.36533.716915.6343
    20攻击方式18.12392.101326.2574
    攻击方式218.25614.627925.064127.9303
    攻击方式333.95658.395030.4609
    下载: 导出CSV

    表  4  不同载体图像生成的特征信息和零水印均衡性测试

    Table  4  Balance test of generated feature information and zero watermarking from different cover images

    特征信息$B$ 最终生成的零水印
    $N_{0}$$N_{1}$$E$$N_{0}$$N_{1}$$E$
    Aerial1 6522 4440.19342 0552 0410.0034
    Barbara2 0832 0130.01712 0862 0100.0186
    Boat1 3662 7300.33302 0552 0410.0034
    Couple1 8252 2710.10891 9982 0980.0244
    Elain2 0882 0080.01952 0852 0110.0181
    Frog2 0272 0690.01032 0422 0540.0029
    Goldhill2 2261 8700.08692 0052 0910.0210
    Zelda1 9432 1530.05132 0782 0180.0146
    平均值1 9012 1950.10262 0512 0460.0133
    下载: 导出CSV

    表  5  不同算法生成的特征信息和零水印均衡性测试

    Table  5  Balance test of generated feature information and zero watermarking from different algorithms

    8幅载体图像均衡性结果的平均值($E$)
    特征信息$B$最终生成的零水印
    本文0.10260.0133
    文献[13]0.00460.0000
    文献[14]0.17070.0130
    文献[15]0.00870.0060
    文献[16]0.01110.0107
    下载: 导出CSV

    表  6  不同载体图像零水印间的相似度

    Table  6  Similarities between the generated zero watermarking from different cover images

    AerialBarbaraBoatCoupleElainFrogGoldhillZelda
    Aerial1.00000.51490.54980.49000.48100.46510.55130.5344
    Barbara0.51491.00000.53300.48780.53000.48970.49440.4850
    Boat0.54980.53301.00000.58810.47560.47340.58940.4465
    Couple0.49000.48780.58811.00000.48800.49510.54610.4292
    Elain0.48100.53000.47560.48801.00000.48320.56590.5051
    Frog0.46510.48970.47340.49510.48321.00000.48900.4912
    Goldhill0.55130.49440.58940.54610.56590.48901.00000.5002
    Zelda0.53440.48500.44650.42920.50510.49120.50021.0000
    下载: 导出CSV

    表  7  不同算法零水印间的相似度

    Table  7  Similarities between the generated zero watermarking from different algorithms

    本文[13][14][15][16]
    最大值0.58940.59520.57980.64180.6292
    最小值0.42920.49000.49540.50170.5266
    平均值0.50520.49710.50930.50400.5044
    方差0.00160.00220.00080.00220.0020
    下载: 导出CSV

    表  8  抗噪声攻击实验结果

    Table  8  Experimental results against noise attacks

    攻击
    方式
    噪声
    强度
    PSNRNC
    本文[13][14][15][16]
    椒盐
    噪声
    0.115.39920.95100.69010.63180.78590.8789
    0.212.36620.92390.62350.57540.74610.8213
    0.310.61690.89320.59270.54580.73160.7741
    0.49.38300.86400.57180.52920.70400.7347
    0.58.40760.82890.55940.51390.67000.6960
    平均值11.23450.89220.60750.55920.72750.7810
    高斯
    噪声
    0.117.17520.97560.79150.70840.89100.9298
    0.213.37110.97120.78850.70940.87690.9263
    0.310.63980.95500.78930.70160.82710.9207
    0.48.76130.92410.77310.68210.73320.9067
    0.57.48530.88040.75000.66170.61970.8783
    平均值11.48650.94130.77850.69270.78960.9124
    下载: 导出CSV

    表  9  抗滤波攻击实验结果

    Table  9  Experimental results against filtering attacks

    攻击
    方式
    窗口
    大小
    PSNRNC
    本文[13][14][15][16]
    中值
    滤波
    3 × 330.07450.99220.91320.90060.96780.9816
    5 × 527.40160.98460.88260.85050.95030.9650
    7 × 726.14520.97540.86520.80890.93530.9482
    9 × 925.13670.96690.84950.77460.92260.9335
    11 × 1124.37520.95900.83480.74290.91060.9207
    平均值26.62660.97560.86910.81550.93730.9498
    维纳
    滤波
    3 × 333.39940.99590.94170.92110.97330.9878
    5 × 530.79470.99150.92370.87620.96000.9745
    7 × 729.34030.98550.90940.83730.94690.9598
    9 × 928.26800.97900.89650.80620.93350.9455
    11 × 1127.43570.97100.88760.77920.92280.9346
    平均值29.84760.98460.91180.84400.94730.9605
    下载: 导出CSV

    表  10  抗JPEG压缩攻击实验结果

    Table  10  Experimental results against JPEG compression attacks

    品质百分数
    (%)
    PSNRNC
    本文[13][14][15][16]
    525.54190.95590.86400.68030.89410.9054
    1027.99580.98560.89980.77870.93640.9513
    1529.32450.98370.91380.81880.94980.9661
    2030.25520.98660.92270.84680.95710.9727
    2530.96690.98610.92740.87210.96070.9780
    3031.54070.99550.93170.88450.96510.9813
    3532.04160.99320.93580.89660.96560.9835
    4032.43190.99220.93810.90190.96800.9864
    4532.81860.99410.94240.91350.96880.9870
    5033.15620.99520.94310.92210.97060.9879
    平均值30.60730.98680.92190.85150.95360.9700
    下载: 导出CSV

    表  11  抗常规图像处理组合攻击实验结果

    Table  11  Experimental results against common image processing combination attacks

    攻击方式PSNRNC
    本文[13][14][15][16]
    中值滤波(5 × 5) +椒盐噪声(0.3)10.53090.89010.57840.52990.72350.7685
    中值滤波(5 × 5) +高斯噪声(0.3)10.46930.95010.74340.64490.81410.9107
    维纳滤波(5 × 5) +椒盐噪声(0.3)10.58010.89260.58360.53410.72440.7699
    维纳滤波(5 × 5) +高斯噪声(0.3)10.53710.95660.76410.65830.82420.9139
    中值滤波(5 × 5) + JPEG压缩(10)26.10200.97620.86760.72120.92190.9341
    维纳滤波(5 × 5) + JPEG压缩(10)27.18700.98190.88350.74250.92640.9429
    JPEG压缩(10) +椒盐噪声(0.3)10.55400.89290.58660.54810.72680.7714
    JPEG压缩(10) +高斯噪声(0.3)10.55600.95510.76100.69200.82280.9099
    JPEG压缩(10) +放大2倍+缩小0.5倍28.35820.98560.90390.81120.94170.9555
    逆时针旋转2度+ JPEG压缩(10)17.63290.86280.68540.64570.80100.8060
    平均值18.85760.93560.76410.68790.84380.8772
    下载: 导出CSV

    表  12  抗偏移行列攻击实验结果

    Table  12  Experimental results against row and column shifting attacks

    攻击方式PSNRNC
    本文[13][14][15][16]
    右偏移2列21.28790.94890.77960.84250.90560.9129
    左偏移2列21.43240.94970.78310.84250.90680.9118
    上偏移2行21.97570.95220.79660.84730.91720.9237
    下偏移2行21.68930.95040.78970.84450.91040.9198
    右偏移2列+上偏移2行19.80690.92710.74440.79190.88270.8882
    左偏移2列+上偏移2行19.84130.92200.74680.79060.87920.8862
    右偏移2列+下偏移2行19.57170.92390.74100.78820.87280.8807
    左偏移2列+下偏移2行19.73640.92480.74230.79100.87470.8837
    平均值20.12910.92960.75280.80120.88400.8917
    下载: 导出CSV

    表  13  抗偏移行列组合攻击实验结果

    Table  13  Experimental results against row and column shifting combination attacks

    攻击方式PSNRNC
    本文[13][14][15][16]
    右偏移2列+上偏移2行+逆时针旋转2度17.14980.85610.67870.69870.82250.8287
    左偏移2列+上偏移2行+逆时针旋转2度17.15850.85540.67600.70190.77640.7808
    右偏移2列+下偏移2行+放大2倍+缩放0.5倍19.96530.92420.74790.78710.87330.8811
    左偏移2列+下偏移2行+缩放0.5倍+放大2倍20.95190.92540.76740.77620.87270.8839
    平均值18.81660.89930.72680.73040.83780.8503
    下载: 导出CSV

    表  14  抗缩放攻击实验结果

    Table  14  Experimental results against scaling attacks

    插值方法攻击方式PSNRNC
    本文[13][14][15][16]
    bilinear缩小0.25倍+放大4倍25.47630.97860.85840.81080.92460.9475
    缩小0.5倍+放大2倍28.34910.99170.89940.88250.94920.9735
    放大4倍+缩小0.25倍34.28620.99760.94830.94540.97420.9898
    放大2倍+缩小0.5倍33.59350.99720.94330.93970.97250.9891
    bicubic缩小0.25倍+放大4倍26.45440.99100.87100.83480.93990.9663
    缩小0.5倍+放大2倍29.90150.99680.91290.91230.96260.9875
    放大4倍+缩小0.25倍39.38010.99890.97100.96990.98590.9954
    放大2倍+缩小0.5倍39.05220.99870.97020.96710.98550.9950
    nearest缩小0.25倍+放大4倍23.13040.95640.82010.69590.90190.9089
    缩小0.5倍+放大2倍25.68810.97900.86530.84560.94300.9522
    放大4倍+缩小0.25倍+$\infty $1.00001.00001.00001.00001.0000
    放大2倍+缩小0.5倍+$\infty $1.00001.00001.00001.00001.0000
    平均值30.53120.99050.92170.90030.96160.9754
    下载: 导出CSV

    表  15  抗仅缩小或放大缩放攻击实验结果

    Table  15  Experimental results against only reduce/enlarge scaling attacks

    插值方法攻击方式NC
    本文[13][14][15][16]
    bilinear缩小0.5倍0.99630.63650.90790.95870.9856
    缩小2倍0.99820.75030.96070.98180.9925
    放大4倍0.99820.56570.96510.98370.9928
    bicubic缩小0.5倍0.99760.63710.92020.96430.9896
    放大2倍0.99890.75070.97950.99140.9965
    放大4倍0.99880.56580.97910.99060.9960
    nearest缩小0.5倍0.97900.62020.84560.94320.9522
    放大2倍1.00000.75131.00001.00001.0000
    放大4倍1.00000.56930.99991.00001.0000
    平均值0.99630.64970.95090.97930.9895
    下载: 导出CSV

    表  16  抗旋转攻击实验结果

    Table  16  Experimental results against rotation attacks

    插值
    方法
    攻击
    方式
    PSNRNC
    本文[13][14][15][16]
    bilinear20.09280.92090.75140.78120.87500.8809
    -1°20.21720.92160.74760.77530.87810.8812
    16.17390.82090.64070.66400.76700.7680
    -3°16.30610.82230.61720.66450.77200.7713
    14.59640.75710.59450.62420.70970.7081
    -5°14.72100.76070.56450.62640.71910.7177
    10°12.86640.66330.53690.58440.62920.6315
    -10°12.96980.67090.51400.58250.64360.6416
    30°10.87970.55820.48800.52350.54870.5541
    -30°10.93890.56340.50930.52360.55250.5489
    bicubic19.87600.92080.74660.78150.87390.8797
    -1°19.99590.92110.74370.77730.87760.8802
    16.07030.82050.63760.66640.76550.7672
    -3°16.19950.82210.61470.66670.77100.7702
    14.52130.75730.59340.62470.70830.7072
    -5°14.64400.76100.56230.62800.71900.7171
    10°12.81520.66310.53590.58470.62900.6313
    -10°12.91750.67080.51470.58470.64340.6410
    30°10.84830.55820.48770.52450.54880.5538
    -30°10.90750.56300.50830.52390.55200.5491
    nearest19.65710.92110.74450.78180.87520.8796
    -1°19.77490.92140.74030.77800.87790.8821
    15.97270.82030.63650.66630.76400.7680
    -3°16.09950.82210.61500.66680.77130.7717
    14.45310.75690.59280.62670.70710.7080
    -5°14.57430.76100.56250.62470.71800.7171
    10°12.77040.66360.53450.58430.62810.6309
    -10°12.87150.67050.51410.58360.64250.6421
    30°10.82070.55790.48950.52120.54930.5539
    -30°10.88000.56340.50890.52240.55300.5486
    平均值14.88110.74580.59490.63560.70900.7101
    下载: 导出CSV

    表  17  本文算法与其他算法抗攻击性能的提高率(%)

    Table  17  Improvement performance against attacks compared this algorithm with other algorithms (%)

    攻击方式[13][14][15][16]
    椒盐噪声47602314
    高斯噪声2136193
    中值滤波122043
    维纳滤波81743
    JPEG压缩71632
    常规信号组合2236117
    偏移行列231654
    偏移行列组合242376
    先缩放$x$倍, 再缩放1/$x$倍71032
    仅缩小或放大$x$倍53521
    旋转251755
    平均值232385
    下载: 导出CSV

    表  18  不同算法在SIPI图像数据集的实验结果

    Table  18  Experimental results on the SIPI image database from different algorithms

    攻击方式PSNR本文[13][14][15][16]
    椒盐噪声11.00860.85870.61640.56900.75420.7940
    高斯噪声12.25000.91700.75990.66110.75330.9042
    中值滤波24.85800.96090.84110.69040.91600.9365
    维纳滤波27.51590.96970.88780.71060.93280.9484
    JPEG压缩29.52650.97700.90910.75140.94560.9663
    常规信号组合15.68690.89590.71450.62110.79290.8560
    偏移行列19.82690.90850.74600.67550.87030.8756
    偏移行列组合17.50260.82220.66880.61840.77120.7743
    缩放29.04960.98430.91050.76220.95360.9721
    旋转13.72180.67980.55670.56650.64220.6416
    平均值20.09470.89740.76110.66260.83320.8669
    下载: 导出CSV

    表  19  不同算法在SIPI图像数据集实验结果的方差

    Table  19  The variance of experimental results on the SIPI image database from different algorithms

    攻击方式本文[13][14][15][16]
    椒盐噪声0.00260.00300.00770.00510.0034
    高斯噪声0.00250.00550.02050.03380.0030
    中值滤波0.00090.00430.02420.00220.0020
    维纳滤波0.00080.00260.02600.00160.0015
    JPEG压缩0.00060.00110.04050.00080.0005
    常规信号组合0.00330.00340.01430.01820.0034
    偏移行列0.00400.00660.01800.00720.0065
    偏移行列组合0.00850.00530.01000.01060.0107
    缩放0.00020.00120.04010.00070.0004
    旋转0.00850.00410.00500.00800.0081
    平均值0.00320.00370.02060.00880.0040
    下载: 导出CSV

    表  20  不同算法构造零水印运行时间(s)

    Table  20  The running time for constructing zero watermarking from different algorithms (s)

    本文[13][14][15][16]
    Aerial0.03430.55540.35416.77820.1607
    Barbara0.03280.54290.34946.74240.1591
    Boat0.03740.54290.35106.82970.1560
    Couple0.03280.54760.34796.82820.1560
    Elain0.03280.54910.35106.80790.1607
    Frog0.03120.54910.34166.78140.1513
    Goldhill0.03430.54440.34946.78140.1576
    Zelda0.03280.56000.35576.81720.1622
    平均时间0.03350.54890.35006.79580.1580
    下载: 导出CSV
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  • 收稿日期:  2016-06-18
  • 录用日期:  2016-11-03
  • 刊出日期:  2018-01-20

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