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

2 Background Concept of Digital Watermarking

3 Framework

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

5 Discrete Cosine Transform (DCT) FDCT IDCT Spatial domain Frequency domain AC DC

6 Just Noticeable Distortion (JND) Frequency domain (DCT) JND

7 Sobel Operator Mask 2 Mask 1 (x, y) Threshold (0) (1)(2)(3) (4)(5) (6)(7)

8 Watermark-random sequence (1/2) original image random sequence={-1,1,-1,-1,1,…,1,-1,1} watermarking key FDCT selected coefficients={9,13,-1,3,-1} modified coefficients={-9,39,-3,-3,1} IDCT

9 Watermark-random sequence (2/2) test image FDCT random sequence={-1,1,-1,-1,1,…,1,-1,1} test key selected coefficients={-9,39,-3,-3,1}

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

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 Position alignment items Block mean value (0) (1) (2) (3) (4) (5) (6) (7) 1238 … 9 … k … (-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 Value alignment item … 9 … k … 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

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

15 Coupling and alignment Coupling pair Alignment

16 Detection scheme pair JND

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

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 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 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 / / / / 7800

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

22 Appendices - DCT

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) * 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 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 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 (1993)

25 Peak Signal-to-Noise Ratio - PSNR