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ELE 488 Fall 2006Image Processing and Transmission

(12 – 7 – 06)

Digital Watermarking

What?

Why?

How?

Attacks, Legal issues

12/7

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Digital Watermark

• What?– secondary information in perceptual media data– examples: picture in picture, words in words, data in data, sound in sound

• Why?

• How?

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Vatican Digital Library

– Founded 1451 by Pope Nicholas V– 150,000 manuscripts (trace back to 300~400 AD)– 1.5 million books– only 2,000 scholars visit each year– security

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from IBM web page

IBM - Vatican Library

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Picture in Picture

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Picture in Picture

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Picture in Picture

http://www.cl.cam.ac.uk/~fapp2/steganography/image_downgrading/

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Is seeing believing?

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All for a royal smile

LONDON, June 21 - One of the official photographs of the wedding of Prince Edward and Sophie Rhys-Jones last Saturday was doctored because Prince Williams ….. did not look happy enough ….

From the New York Times, June 22, 1999

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E-files: binary “images”

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Authorized and unauthorized modification

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Document Authentication

alter

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Words in Words

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Digital Watermark

• What?– Secondary information in perceptual media data

• Why?– To convey other information

– To Detect Alteration

• Easy to modify authentication

• Easy to copy without degradation ownership

• Seeing is believing?

• How?

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Picture in Picture

http://www.cl.cam.ac.uk/~fapp2/steganography/image_downgrading/

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Additional Functionality – error concealment

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How can watermark help to detect alteration?

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Document Authentication

– Embed prescribed pattern or content features beforehand– Verify hidden data’s integrity to decide on authenticity

(f)

alter(a)

(b)

(g)

after alteration

(e)

(c)

(d)

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Document Authentication

– Embed prescribed pattern or content features beforehand– Verify hidden data’s integrity to decide on authenticity

(f)

alter(a)

(b)

(g)

after alteration

(e)

(c)

(d)

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Digital Watermark

• What?– Secondary information in perceptual media data

• Why?– To Detect Alteration

• Easy to modify authentication

• Easy to copy without degradation ownership

• Seeing is believing?

– Convey other information

• How? – Insertion and detection

• Replacing LSB

• Fragile watermark

• Robust watermark

• Binary images (documents)

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Picture in Picture

http://www.cl.cam.ac.uk/~fapp2/steganography/image_downgrading/

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Replacing LSBU

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Replacing LSBs

Replace 6 LSBs with Pentagon’s 6 MSBsUM

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Fragile WM to Detect Modification

Yeung & Mintzer ICIP’97

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Fragile WM - Pixel-domain Table-lookup -

• Pro: simple; be able to localize alteration extracted wmk from altered image

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# of changeable coeff: 0-30 / blk embed 1bit/blk by repetition

Embed in Compressed Domain

• limit LUT runs of 1’s and 0’s• DC and small coeffs not modified

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Difficulties: smooth region

– smooth region difficult to embed, uneven embedding

– solutions: backup, shuffling

– use ‘error difusion’ in pixel domain embedding

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Uneven embedding capacity

0 5 10 15 20 25 30 350

0.05

0.1

0.15

0.2

0.25

# of embeddable coefficients per interval: (--) before shuffle (-) mean of shuffle (..) mean+/-std

% o

f int

erva

ls

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– embedding rate … >= 1 bit / block

Wu-Liu Scheme: shuffling (cont’d)

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Embedding and Extraction

– What to embed? @

• meaningful pattern: facilitate quick visual check and locate alteration

• low-level content-based features to help detect alteration

ELE 488 F06 Fridrich & Goljan ICIP 99

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• Ideas– Place wmk in perceptually significant spectrum– use random vector as wmk to avoid artifacts

– scaling N=1000 largest AC coeff. {vi} by a random factor

– wi – iid, zero mean, unit variance

• Embedding: vi’ = vi(1+a wi), a ~ 0.1

• How to extract w ?

2D DCT sort v’=v (1+a w) IDCT & nomalize

original image N largest coeff.

other coeff.

marked imageN random numbers

wmk

seed

Robust Watermark - Spread Spectrum Embedding(NEC scheme, Cox’s scheme)

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• Detection: based on hypothesis testing

– measure and threshold the similarity between Y & W

DCT

compute similarity

thresholdtest image

decision

wmkDCT select N

largest

original unmarked image

select N largest

preprocess

k watermar

watermarkno

:1

:0

NWYH

NYHXXY

-

YY

WYWYsim

,

,),(

-orig X

test X’

X’=X+W+N ?

X’=X+N ?

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Random sequence of 1 and –1

1 1 1 -1 -1 1 -1line up x) 1 1 1 -1 -1 1 -1 1 1 1 1 1 1 1 sum = 7

1 1 1 -1 -1 1 -1 shift 1 1 1 -1 -1 1 -1 1 1 -1 1 -1 -1 sum = 0 1 1 1 -1 -1 1 -1 0shift 2 0 1 1 1 -1 -1 1 -1 1 -1 -1 -1 1 sum = -1shift 3 , sum = 0shift 4 , sum = -1shift 5 , sum = 0shift 6, sum = -1 results symmetric if shifted to the left.

Correlation: -1 0 -1 0 -1 0 7 0 -1 0 -1 0 -1

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0 20 40 60 80 100-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200-50

0

50

100

100 binary random numbers

0 50 100 150 200-30

-20

-10

0

10

20

30

correlation

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Two binary random sequences

0 20 40 60 80 100-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200-40

-30

-20

-10

0

10

20

cross correlation

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0 500 1000 1500 2000-50

0

50

100

150

200

250

300

350

0 500 1000 1500 2000-60

-40

-20

0

20

40

60

1000 random numbers (-1, 1)

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0 500 1000 1500 2000-30

-20

-10

0

10

20

30

40

0 20 40 60 80 100-1.5

-1

-0.5

0

0.5

1

1.5

x: 1 or -1, s = sine signal, sx = s+.05*x, correlate x & sx

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Cox’s Scheme (cont’d)

• Robustness:– (claimed) scaling, JPEG, dithering, cropping, “printing-

xeroxing-scanning”, multiple watermarking

• Comment:– must store original unmarked image “private wmk”

– perform registration if necessary

– adjustable parameters: N and

Distortion none scale25%

JPG10%

JPG 5% dither crop25%

print-xerox-scan

similarity 32.0 13.4 22.8 13.9 10.5 14.6 7.0 threshold = 6.0 (determined by setting false alarm probability)

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Examples ... wmk & distortions

Original JPEG 10% (~30:1 compression) lowpass

– Robust watermark are designed to survive distortions:

markedorig.wmk

distorteddistortion

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Compare NEC & Bell schemes

Orig.? NEC ? Bell – PU ?

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Compare NEC & Bell schemes (cont’d)

NEC Bell - PU

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Document (AT&T)

from http://www.acm.org/~hlb/publications/dig_wtr/dig_watr.html

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Original Altered (flipx=2000)

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The Difference

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References

• F. Mintzer, G.W. Braudaway, M.M. Yeung, “Effective and Ineffective Digital Watermarks”, IEEE ICIP 97

• Cox, J. Kilian, T. Leighton, T. Shamoon: “Secure Spread Spectrum Watermarking for Multimedia'', IEEE Trans Image Processing, Dec 1997

• M Wu, B Liu, “Watermarking for image authentication”, ICIP 98.

• M. Wu, B. Liu, “Data Hiding in Binary Images for Authentication and Annotation", IEEE Trans Image Processing, August 2004.

• J. Fridrich, M. Goljan,”Image with Self-correcting Capabilities, ICIP 1997