Download presentation
Presentation is loading. Please wait.
1
Watermarking MPEG-4 2D Mesh Animation in the Transform Domain
報告：梁晉坤 指導教授：楊士萱 2003/12/4
2
Outline MPEG-4 2D Mesh Animation Digital Watermarking
Wavelet Transform Discrete Cosine Transform Singular Value Decomposition Simulate Results Conclusion
3
MPEG-4 2D Mesh Animation MPEG-4 synthetic visual coding allows 2D-Mesh and 3D-Mesh represent generic objects. MPEG-4 2D Mesh animation consists of a sequence of polygon models, little watermarking techniques are proposed for it. Mesh Object Plane, MOP
4
Mesh Object Plane A Sequence of MOPs
5
Mesh Types Uniform Mesh Delaunay Mesh
6
Digital Watermarking It is the process of embedding extra data, the watermarking signal, to the digital data. Watermark species visible and invisible robust and fragile public and private spatial and transform domain
7
Applications copyright protection, fingerprinting, copy control, data authentication, broadcast monitoring Basic properties transparency, robustness, security
8
Watermark Modify on the Spatial Domain Watermarked Data Original Data Original Data Transform to the Transform Domain Watermark Inverse Transform to the Spatial Domain Modify on the Transform Domain Watermarked Data FFT, DCT, Wavelet Transform, SVD, etc.
9
Wavelet Transform Realizing discrete wavelet transform by “Filter Bank” h0(t) h1(t) 2 y1 y0 X 2 g0(t) g1(t) X’ Analysis Filter Synthesis Filter
10
Multi-resolution Representation
Original L1 H1 L2 H2 …… Lp Hp
11
Embedding Procedure Decomposing 2D mesh animation by multi-resolution wavelet transform p level decomposition generate (p+1) subbands, L-p, H-p, H-(p-1), … , H-1 Computing Euclid distance for L-p subbband Choosing k largest coarse coefficients for watermarking in L-p subband
12
Embedding Procedure(Cont.)
Embedding component selection Select larger component(X or Y) The same, select X component Perturbing selected component according to watermark Bits Bit=1, add a positive value(Intensity) Bit=0, sub a negative value(Intensity)
13
Wavelet Decomposition
L-p Original 2D Mesh Animation Wavelet Decomposition Compute Euclid Distance H-p,H-(p-1),…,H-1 Select Embedding Location I Watermark Embedding -I Watermarked 2D Mesh Animation Inverse Wavelet Decomposition
14
Extraction Procedure Decomposing original and attacked 2D mesh animation by multi-resolution wavelet transform p level decomposition generate (p+1) subbands, L-p, H-p, H-(p-1), … , H-1 Computing Euclid distance from original mesh L-p subbband Find out suspected coarse vectors Finally, watermark is extracted from these coarse vectors
15
Wavelet Decomposition Wavelet Decomposition
Original 2D Mesh Animation Watermarked 2D Mesh Animation Wavelet Decomposition Wavelet Decomposition L-p Watermark Extraction L’-p Extracted Watermark
16
WV’: attacked coarse vectors WV: original coarse vectors
If(WV’i< WVi) then wi=0 If(WV’i> WVi) then wi=1
17
Discrete Cosine Transform
X ={X0,X1,…,XN-1} of length N= 2p Y ={Y0,Y1,…,YN-1}, Y is the transformed sequence of X,
18
DCT IDCT
19
Embedding Procedure Dividing 2D Mesh to a lot of point sequences(each sequence include X,Y component, and its length N=2p) Doing DCT to each point sequences, select a maximum absolute value from X,Y component(DC value), and push to DCTV Choosing k largest DC values from DCTV for watermarking embedding
20
P seq.1. DCT Push to P seq.2. DCTV P seq.n. P’ seq.1. IDCT P’ seq.2.
Original 2D Mesh Animation P seq.1. DCT Push to DCTV P seq.2. P seq.n. Select Embedding Location I Watermark Embedding Watermarked 2D Mesh Animation P’ seq.1. -I IDCT P’ seq.2. P’ seq.n.
21
Extraction Procedure Dividing original mesh and attacked mesh to a lot of point sequences Doing DCT to each point sequences, find out suspected DC values from original mesh point sequences Watermarking is extracted from the DC values
22
P’ seq.1. P seq.1. P’ seq.2. P seq.2. P’ seq.n. P seq.n. Watermarked
2D Mesh Animation P’ seq.n. Original 2D Mesh Animation P seq.n. DCT DCT DCTV Watermark Extraction DCTV’ Extracted Watermark
23
WDC’ value: attacked DC value WDC value: original DC value
If(WDC’i< WDCi) then wi=0 If(WDC’i> WDCi) then wi=1
24
Singular Value Decomposition
X:mxn, U:mn, S:n n, V:n n (Matrices) X=U S VT where U,V are unitary matrices(UUT=UTU=I), S is a Singular matrix The d singular values on the diagonal of S are the square roots of the nonzero eigenvalues of both AAT and ATA
25
The main property of SVD is the singular values(SVs) of an Matrix(or image) have very good stability, that is, when a small perturbation is added to an Matrix, its SVs do not change significantly.
26
SVD Window Length= L needs 2L-1 point sequences
27
Embedding Procedure AU S VT Sw=S+aW ,where W{0,1} AwU Sw VT Extraction Procedure Compute U, V and S as above AaU Sa VT D=UT Aa V Sa, Sa Sw W=(D-S)/a
28
Push to SVDV SVD Do_Matrix Do_IMatrix ISVD Original 2D Mesh Animation
Select Embedding Location I Watermark Embedding Watermarked 2D Mesh Animation -I Do_IMatrix ISVD
29
do Matrix=B do Matrix=A Assume B=U*Sa*Vt Watermarked 2D Mesh Animation Original 2D Mesh Animation D=Ut*B*V Sa, Sa Sw SVD=> A=U*S*Vt Watermark Extraction D S Extracted Watermark
30
Simulate Results Compute for robustness BER, bit error rate
Compute for transparency MMSE , motion mean square error
31
Attacks Random noise Affine Smoothing Enhancement and Attenuation Time warping Simplifying
32
Transform methods SVD DCT D_4 D_8 Lift5_3 Conv9_7 Lazy Haar
33
Test1 Mesh12 Mesh12 128 MOPs, each MOP has 120 points and 187 triangles Watermark, 127 bits PN code Quality=0.005 (MMSE) Simplifying and Scale Coefficient using Conv97 at LV =4
34
Smoothing Attack({1/4,1/2,1/4})
Type BER P=2 P=4 P=6 D_4 D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
35
Affine Attack-1( 1.3,0,(12,0) ) Type BER P=2 P=4 P=6 D_4 D_8 Lift5_3
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
36
Affine Attack-2( 1,25,(0,5) ) Type BER P=2 P=4 P=6 D_4 D_8 Lift5_3
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
37
Affine Attack-3( 0.7,65,(-11,-9) ) Type BER P=2 P=4 P=6 D_4 0.212598
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
38
SCAttack, all good Time warping Attack,all good
39
RN Attack-10% TYPE BER P=2 P=4 P=6 N=1 N=2 D_4 0.070866 D_8 0.039370
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
40
RN Attack-20% TYPE BER P=2 P=4 P=6 N=1 N=2 D_4 0.062992 0.023622 D_8
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
41
RN Attack-30% TYPE BER P=2 P=4 P=6 N=1 N=2 D_4 0.0393701 0.125984 D_8
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
42
RN Attack-40% TYPE BER P=2 P=4 P=6 N=1 N=2 D_4 0.0393701 0.086614
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
43
RN Attack-50% TYPE BER P=2 P=4 P=6 N=1 N=2 D_4 0.023622 0.133858
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
44
Simplifying Attack Type BER P=2 P=4 P=6 D_4 D_8 Lift5_3 Conv9_7 Lazy
D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
45
Test2 Bream Bream 32 MOPs, each MOP has 165 points and 270 triangles
Watermark, 31 bits PN code Quality=0.005 (MMSE) Simplifying and Scale Coefficient using Conv97 at LV =2
46
TYPE Embedding time(sec) Execution Time(sec) P=2 P=4 P=6 D_4 D_8 Lift5_3 Conv9_7 Lazy Haar DCT SVD
47
Conclusion SVD is robust, but consumes longer time
Lazy is the worst wavelet filter for watermarking Acceptable quality and robust to attacks
Similar presentations
![Www.fakengineer.com [1] AN ANALYSIS OF DIGITAL WATERMARKING IN FREQUENCY DOMAIN.](/1/277349/big_thumb.jpg "Www.fakengineer.com [1] AN ANALYSIS OF DIGITAL WATERMARKING IN FREQUENCY DOMAIN.>")
