1. A robust associative watermarking technique based on similarity diagrams Source: Pattern Recognition, Vol. 40, No. 4, pp. 1355-1367, 2007 Authors: Jau-Ji Shen and Po-Wei Hsu

2. 2 Background Concept of Digital Watermarking

3. 3 Framework

4. 4 Introduction Just Noticeable Distortion Sobel Operator Association Rules Discrete Cosine Transform Original Image Watermark Embedded Image

5. 5 Discrete Cosine Transform (DCT) 139 141136135 133132 136137138135133 132 136134135 136134132133 136135136 135 132134 135 137 134132136 134 137 136135134138 135 138 137136 144 137 138140138139143147 FDCT IDCT Spatial domain 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 Frequency domain AC DC

6. 6 Just Noticeable Distortion (JND) 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 Frequency domain (DCT) 02344368 12455794 34524579 345229810 55663789 4454678 666655 12 78798101220 JND

7. 7 Sobel Operator 121 000 -2 10 20-2 10 121 000 -2 Mask 2 Mask 1 (x, y) Threshold 0-2 10 210 -2 000 121 012 01 -20 10 20-2 10 01 -202 01 210 10 0 -2 0 01 012 (0) (1)(2)(3) (4)(5) (6)(7)

8. 8 Watermark-random sequence (1/2) 139 141136135 133132 136137138135133 132 136134135 136134132133 136135136 135 132134 135 137 134132136 134 137 136135134138 135 138 137136 144 137 138140138139143147 original image 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 random sequence={-1,1,-1,-1,1,…,1,-1,1} watermarking key FDCT 1082-3-5330 -939-34-4001 -9-2-3-2 101 3 1 10 4011 0 0 10000020 1 20101 00012 00 selected coefficients={9,13,-1,3,-1} modified coefficients={-9,39,-3,-3,1} IDCT

9. 9 Watermark-random sequence (2/2) 140141 138136134132131 140138136135133134132131 137138135 136134132133 136135136 135 132134 135 137 134132136 134 138 137136135139 136 138139136135134143 139 140141137138142146 test image 1082-3-5330 -939-34-4001 -9-2-3-2 101 3 1 10 4011 0 0 10000020 1 20101 00012 00 FDCT random sequence={-1,1,-1,-1,1,…,1,-1,1} test key selected coefficients={-9,39,-3,-3,1}

10. 10 Association Rules (K-itemset) Transaction Database TIDItems T1A,B,E,F T2A,B,C,E,F T3B,D,E

11. 11 Key Concept Just Noticeable Distortion Sobel Operator Association Rules [b1 I (k), b2 I (k), b3 I (k), b4 I (k)] [b1 W (k), b2 W (k), b3 W (k), b4 W (k)] Discrete Cosine Transform Original Image Watermark Embedded Image

12. 12 Position alignment items 120809095100 120 115758590105 115 100806580 9070100 120908075 807585 1101006080130110120110 1001159580125120 115 9095100105120135105110 95100105120 130125120 Block mean value 121 000 -2 0 -2 10 210 -2 000 121 012 01 -20 10 20-2 10 01 -202 01 210 10 0 -2 0 01 012 (0) (1) (2) (3) (4) (5) (6) (7) 1238 … 9 … k … 57 64 6362 (-1)*65+(-2)*80+(-1)*80 +0*80+0*75+0*75 +1*60+2*80+1*130=45 random sequence={1,1,-1,…,1,-1,-1…,-1,-1,1} watermark W watermarking key

13. 13 Value alignment item 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 1238 … 9 … k … 57 64 6362 DCT transform AC={0, -1, 2, 77, 9, 13, -3,…, -9, 20, 3,…, 33, 5, 0} sort(abs(AC))={77,33,20,…,13,9,9,5,…,1,0,0} select first C elements 00000000 -913000000 90000000 00000000 00000000 00000000 00000000 00000000 01 1 11 1 1 111 1 1 111 1 11 1111 1 1 11111111 1 11111 11111 11 13-9 9

14. 14 Quantization and sieve Quantization (M 1 =8, M 2 =7) Sieve Quantization 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 smooth block

15. 15 Coupling and alignment Coupling 00000000 -913000000 90000000 00000000 00000000 00000000 00000000 00000000 01 1 11 1 1 111 1 1 111 1 11 1111 1 1 11111111 1 11111 11111 11 02344368 12455794 34524579 345229810 55663789 4454678 666655 12 78798101220 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 -10 15 12 pair Alignment

16. 16 Detection scheme 1082-5330 -913-34-4001 9-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 00000000 -913000000 90000000 00000000 00000000 00000000 00000000 00000000 1082-5330 -1015-34-4001 12-23 101 3 10 4011 0 0 10000020 1 20101 00012 00 01 1 11 1 1 111 1 1 111 1 11 1111 1 1 11111111 1 11111 11111 11 pair JND

17. 17 Experiments (1/4) 256x256 image, 208x208 watermark PSNRPSNR=36.062PSNR=37.222PSNR=35.563

18. 18 Experiments (2/4) 200 test keys (100 th key) more blurring more sharpeningbrightness adjustment(+40) Gaussion noise (σ 2 =20) cutting (50%) JPEG compression (1%)

19. 19 Experiments (3/4) False-negative errors: an embedding image while watermark not being detected False-positive errors: a non-watermarked image but extracted result is yes 200 test keys (100 th key)

20. 20 Experiments (4/4) Comparisons of the proposed method and Fotopoulos’s method. Image processing attack type Our methodFotopoulos’s method False- negative errors False- positive errors False- negative errors False-positive errors Attack-Free0 / 600 Blurring0 / 600 Sharpening0 / 600 Brightness adjustment (+40)0 / 600 Gaussion noise (σ 2 =10, 15, 20)0,0,0 / 600 0,0,1 / 600 Cut (70%, 60%, 50%)0,0,10 / 6000,0,0 / 600 JPEG compression (20%, 10%, 1%)0,0,0 / 600 0,138,597 / 600 0,0,0 / 600 Total10 / 78000 / 7800735 / 78001 / 7800

21. 21 Conclusions A novel associative watermarking concept is proposed Robust against different attacks Original image is needed while detecting watermark

22. 22 Appendices - DCT

23. 23 Appendices - JND JND(x,y)=max{ F1(bg(x,y), mg(x,y)), F2(bg(x,y)) } F1(bg(x,y) ， mg(x,y)) = mg(x,y) ‧ α(bg(x,y) + β(bg(x,y)) α(bg(x ， y)) = bg(x,y) * 0.0001 + 0.115 β(bg(x ， y)) = λ – bg(x ， y)* 0.01 for 0 ≦ x ≦ H and 0 ≦ y ≦ W 其中 bg(x,y) 是 (x, y) 位置之平均亮度值， mg(x, y) 是 (x, y) 位置周圍透過以下四個梯度運算子 G k ，在四個方 向上計算最大平均加權亮度之差值。 bg(x,y) 及 mg(x,y) 計算式分列如下 : 表 1.1 計算 mg(x,y) 所使用四個梯度算子 0000000100001000100 138310830000380030-30 00000130 -3031080-80 -3-8-300-3-800 -300030 0 0000000000-8-3000100 G1G1 G2G2 G3G3 G4G4 T ， γ ，和 λ 則分別設定為 17, 3/128 和 1/2 。       127 y)bg(x,for 127),(for yxbg         3, )127)),( ‧(‧(,3 )127/),((1 ‧(‧( )),((2 2 1 yxbg yx T yx F 

24. 24 DCT version of JND formula is a constant whose value is 0.649, stands for the DC coefficient value of the k th block in the image, is the average value of the DC coefficients from all the image blocks, is the value of the element in position (i, j) of the JPEG quantization matrix, is a constant set to be 0.7, and finally is the coefficient value of the k th block of the image. A. B. Watson, “DCT quantization matrices visually optimized for individual images,” Proc. SPIE, Vol. 1913 (1993) 202-216.

25. 25 Peak Signal-to-Noise Ratio - PSNR