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VIPER Slide 1
Detection of Image Alterations Using Semi-fragile Watermarks
Eugene T. Lin†, Christine I. Podilchuk‡ and Edward J. Delp†
†Purdue University School of Electrical and Computer Engineering
Video and Image Processing Laboratory (VIPER)West Lafayette, Indiana
‡Bell Laboratories, Lucent TechnologiesMurray Hill, New Jersey
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VIPER Slide 2
Overview
• Introduction
– Image authentication
– Fragile watermarks
– Robust watermarks
– Semi-fragile watermarks
• Description of proposed technique
• Results
• Conclusion
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VIPER Slide 3
Image Authentication
• Identify the source of an image
• Determine if the image has been altered
• If so, locate regions where alterations have occurred
• Authentication watermark
– watermark is imperceptible under normal observation
– allows user to determine if image has been altered after mark embedding
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VIPER Slide 4
Fragile Watermarks
• Watermark is rendered undetectable after slightest modifications to marked content
• Typically able to localize alterations with high degree of precision
• Sensitivity achieved through use of hash functions
• Problem: if lossy compression is applied to marked image, mark is destroyed even though compressed image remains perceptually similar
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VIPER Slide 5
Robust Watermarks
• Resists removal attempts
• Examines large regions of image, limited localization of alterations
• Robustness typically achieved through spread-spectrum techniques
• Problem: robust watermark may remain even after alterations that change the visual message conveyed by the image
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VIPER Slide 6
Semi-Fragile Watermarks
• Able to detect and localize significant “information altering” transformations (feature replacement)
• Able to tolerate some degree of “information preserving” transformations (lossy compression)
• Suitable in authentication applications where legitimate use includes lossy compression or other image adjustment by users
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VIPER Slide 7
Semi-Fragile Watermarks
• Challenges for fragile watermark semi-fragile watermark:
– LSB plane embedding not tolerant to compression
– Cryptographic hash functions too sensitive
• Challenges for robust watermark semi-fragile watermark:
– Reduce region size used in mark detection but retain enough SNR to achieve reliable detection
– Boundary effects
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VIPER Slide 8
Description of Proposed Technique
• Watermark construction
– DCT construction, spatial embedding
• Watermark detection
– Based on differences of adjacent pixel values
– Most natural images contain large regions of relatively smooth features
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VIPER Slide 9
Watermark Construction
DCDC
1 2 3 4 5 6 7
1234567
= Mark coefficient is set tozero.
= Mark coefficientsampled from PRNG(zero mean, 2 variance)
8x8 DCT Block
DCT Watermark Generation
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VIPER Slide 10
Watermark Construction
• After watermark is constructed in DCT domain, it is transformed to spatial domain and embedded
DCT watermark Generation
IDCT
Original Image
+Marked Image
W
X
Y=X+W
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VIPER Slide 11
• Independent detection performed on each block, for localizing altered blocks
• Define two operators:
Watermark Detection
Blocksize x if
} 1-Blocksize,1,2, { xif
0
),1(),()),((
yxByxByxBCOL
Blocksize y if
} 1-Blocksize,1,2, {y if
0
)1,(),()),((
yxByxByxBROW
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VIPER Slide 12
Example of Differential Operators
3541
3415
1533
7411
),( yxB
0215
0134
0620
01132
)(BCOL
0000
6954
4122
6124
)(BROW
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VIPER Slide 13
Watermark Detection
• Tb = Block of image being tested
• Wb = Corresponding block of watermark image
• Detector uses both row and column differences:
)),(()),((
)),(()),((
*
*
yxWyxWW
yxTyxTT
bROWbCOLb
bROWbCOLb
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VIPER Slide 14
Block Test Statistic
• Tb* and Wb* are correlated to compute block test statistic b:
))(( ****
**
bbbb
bbb
WWTT
WT
b T: Block is likely authenticb < T: Block is likely altered.
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VIPER Slide 15
Results - Gradient
Original “Gradient” Altered “Gradient”
Total Blocks: 682, Altered:300 (44%)
Detector Block size:16x16, embedding =5.0
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VIPER Slide 16
Results - Gradient
0.00.10.20.30.40.50.60.70.80.91.0
0.0 0.5 1.0 1.5 2.0 2.5Image Bit Rate (bits/pixel)
Dete
cti
on
Sta
tisti
c V
alu
e
Mean Unaltered Mean Altered
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VIPER Slide 17
Results - Gradient
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1
Threshold Value
Pe
rce
nt
Co
rre
ct
De
tec
tio
ns
JPEG-90 JPEG-50 JPEG-30
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VIPER Slide 18
Results - Sign
Original “Sign” Altered “Sign”
Total Blocks: 1536, Altered:77 (5%)
Detector Block size:16x16, embedding =5.0
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VIPER Slide 19
Results - Sign
0.00.10.20.30.40.50.60.70.80.91.0
0.0 0.5 1.0 1.5 2.0 2.5Image Bit Rate (bits/pixel)
Det
ecti
on
Sta
tist
ic V
alu
e
Mean Unaltered Mean Altered
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VIPER Slide 20
Results - Sign
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1
Threshold Value
Pe
rce
nt
Co
rre
ct
De
tec
tio
ns
JPEG-90 JPEG-50 JPEG-30
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VIPER Slide 21
Results - Money
Original “Money” Altered “Money”
Total Blocks: 570, Altered:143 (25%)
Detector Block size:16x16, embedding =5.0
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VIPER Slide 22
Results - Money
0.00.10.20.30.40.50.60.70.80.91.0
0.0 0.5 1.0 1.5 2.0 2.5Image Bit Rate (bits/pixel)
Det
ecti
on
Sta
tist
ic V
alu
e
Mean Unaltered Mean Altered
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VIPER Slide 23
Results - Money
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1
Threshold Value
Pe
rce
nt
Co
rre
ct
De
tec
tio
ns
JPEG-90 JPEG-50 JPEG-30
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VIPER Slide 24
Results - Girls
Original “Girls”
Altered “Girls”
Total Blocks: 5704, Altered:951 (17%)
Detector Block size:16x16, embedding =5.0
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VIPER Slide 25
Results - Girls
0.00.10.20.30.40.50.60.70.80.91.0
0.0 0.5 1.0 1.5 2.0 2.5Image Bit Rate (bits/pixel)
Det
ecti
on
Sta
tist
ic V
alu
e
Mean Unaltered Mean Altered
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VIPER Slide 26
Results - Girls
0
20
40
60
80
100
0 0.2 0.4 0.6 0.8 1
Threshold Value
Pe
rce
nt
Co
rre
ct
De
tec
tio
ns
JPEG-90 JPEG-50 JPEG-30
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VIPER Slide 27
Detection Performance
Embed: =5.0
Detection:T=0.1
blocksize=16x16JPEG-60
bitrate=0.90 bpp
93% correct detection4% false positive
17% misses
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VIPER Slide 28
Conclusions
• A semi-fragile watermarking technique was proposed which classifies about 70%of blocks correctly for moderate JPEG compression, 90% for light JPEG compression
• Detector has problems with edges and textures
• Future work:
– Integrate a visual model to embed mark at higher strengths in textured areas