UC Lab Kyung Hee University, South Korea

January 09 , 2015

UC Lab Kyung Hee University, South Korea 2

UC Lab Kyung Hee University, South Korea 3

• Millions of images are shared every day through the SNS

• Many of these images end up in the hands of unknown

people that use them in an illegal and malicious manner

• Mechanisms for ensuring the ownership and protecting the

copyright are utterly required to settle potential disputes

ImageWatermarking

UC Lab Kyung Hee University, South Korea 4

Convenience

Imperceptibility

Robustness

The information should be extracted from the original image

A watermark has to be imperceptible

A watermark needs to be robust against image modifications

visualization

frequency domain

• Quality

Optimal color channel selection

• Accuracy rate in the extraction process

Optimal threshold based on the Otsu method.

UC Lab Kyung Hee University, South Korea 5

UC Lab Kyung Hee University, South Korea 6

Article Key concept Limitations

Xiang-yang [2012] Fourier transform

Least square support vector

machine (LS-SVM)

High computation time for LS-SVM training.

Niu [2011] Nonsubsampled coutourlet

transform (NSCT)

Support vector regression (SVR)

Low performing NSCT and computation time in

extraction process.

Song [2012] Curvelet transform

Coefficient quantization technique

Weakness under lossy JPEG compression

Chou [2010] Wavelet transform

Just noticeable color difference

(JNCD)

Weakness under geometric operations and hue

modification.

UC Lab Kyung Hee University, South Korea 7

Color Images

4-DWTCoeffientBlocking

CoeffientDifference

Optimum Selection

Embedding Rule

Coefficient Unblocking

4-IDWTEmbedded

Image

Binary Watermark

Bit shufflingCombined

Key

Recovered Watermark

Bit Reshuffling

Extraction Rule

Coefficient Difference

Coefficient Blocking

4-DWTModified Image

Adaptive threshold

Otsu method

Channel

Attacks

Embedding process

Extraction process

UC Lab Kyung Hee University, South Korea 8

Color Images

4-DWTCoefficient Blocking

Coefficient Difference

Optimum Selection

Embedding Rule

Coefficient Unblocking

4-IDWTEmbedded

Image

Binary Watermark

Bit shufflingCombined

Key

HL4

(C(HL,i))

LH4

(C(LH,i))

Block 1

C(HL,1 )

Block 2 Block n

C(HL,2) C(LH,1 ) C(LH,2)C(HL,n) C(HL,n)

Coefficient difference

Nu

mb

er o

f blo

cks Before embedding

The embedding process

Coefficient difference

Nu

mb

er o

f blo

cks

After embedding

0-bits

1-bits

y1 y2

∆𝑖,𝑘 (= 𝐶𝐿𝐻𝑖,𝑘 − 𝐶𝐻𝐿𝑖,𝑘 )

∆𝑖,𝑘→ ∆𝑖,𝑘𝑆

𝛻𝑖0 = 𝑦1 − ∆𝑖,𝑘

𝑆 𝑦1 =1

𝑁0 𝑘=13 𝑖=1

𝑁0 ∆𝑖,𝑘𝑆

𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 + 𝛻𝑖0 ; ∀𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 ≥ 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡

𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 + 𝛻𝑖0 ; ∀𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 < 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡

UC Lab Kyung Hee University, South Korea 9

LL4 HL4

LH4 HH4

HL4

(C(HL,i))

LH4

(C(LH,i))

Block 1

C(HL,1 )

Block 2 Block n

C(HL,2) C(LH,1 ) C(LH,2)C(HL,n) C(HL,n)

The embedding process

UC Lab Kyung Hee University, South Korea 10

∆1,𝑅 ∆1,𝐺 ∆1,𝐵

∆2,𝑅 ∆2,𝐺 ∆2,𝐵

⋮ ⋮ ⋮

∆𝑛−1,𝑅 ∆𝑛−1,𝐺 ∆𝑛−1,𝐵

∆𝑛,𝑅 ∆𝑛,𝐺 ∆𝑛,𝐵

∆𝑖,𝑘 − 𝑦1 ; ∀ 0 − bit

∆𝑖,𝑘 − 𝑦2 ; ∀ 1 − bit

UC Lab Kyung Hee University, South Korea 11

The extraction process

Embedded Image

Recovered Watermark

Bit Reshuffling

Extraction Rule

Coefficient Difference

Coefficient Blocking

4-DWTModified Image

Adaptive threshold

Otsu method

Attacks

HL4

(C(HL,i))

LH4

(C(LH,i))

Block 1

C(HL,1 )

Block 2 Block n

C(HL,2) C(LH,1 ) C(LH,2)C(HL,n) C(HL,n)

Coefficient difference

Nu

mb

er o

f blo

cks

After embedding

Optimal threshold0-bits

1-bits

𝛻𝑖1 = 𝑦2 − ∆𝑖,𝑘

𝑆 𝑦2 =1

𝑁0 𝑘=13 ∆𝑖=𝜆𝑁1,𝑘

𝑆

∆𝑖,𝑘𝑆 < 𝑦2

𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 + 𝛻𝑖1

𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 − 𝛻𝑖0 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 ≥ 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡

𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 − 𝛻𝑖1

𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 + 𝛻𝑖0 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 < 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡

∆𝑖,𝑘𝑆 ≥ 𝑦2

𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐿𝐻𝑖,𝑘_𝑜𝑝𝑡𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡 = 𝐶𝐻𝐿𝑖,𝑘_𝑜𝑝𝑡

UC Lab Kyung Hee University, South Korea 13

(a) (b) (c) (d)

(e) (f) (g) (h)

UC Lab Kyung Hee University, South Korea 14

Table 1: Quality of embedded images

Image CPSNR (dB) SSIM

Airplane 45.81 0.992

Girl 53.13 0.999

House 43.41 0.995

Lena 48.17 0.999

Mandrill 46.75 0.999

Peppers 44.57 0.999

Sailboat 43.73 0.998

Splash 55.28 0.999

Image quality after embedment

Original Watermarked

UC Lab Kyung Hee University, South Korea 15

Watermark robustness after extraction (NC value)

0.4

0.5

0.6

0.7

0.8

0.9

1

Non-attack Scaling Cropping 25% Rotation (0.5) Gaussian noise

Geometric attacking

Airplane Girl House Lena Mandrill Peppers Sailboat Splash

0.4

0.5

0.6

0.7

0.8

0.9

1

Histogram

equalization

Average filter 7x7 Median filter 7x7 Gaussian filter 7x7

Non-geometric attacking

Airplane Girl House Lena Mandrill Peppers Sailboat Splash

0.4

0.5

0.6

0.7

0.8

0.9

1

JPEG QF=10% JPEG QF=20% JPEG QF=40% JPEG QF=60%

Lossy JPEG compression

Airplane Girl House Lena Mandrill Peppers Sailboat Splash

UC Lab Kyung Hee University, South Korea 16

0.4

0.5

0.6

0.7

0.8

0.9

1

Scaling Cropping

20%

Rotation (5) Gaussian

noise

Median

filter 3x3

Gaussian

filter 3x3

JPEG

QF=30%

JPEG

QF=40%

JPEG

QF=70%

Robustness comparison - NC

Niu [7] Proposed

40.71

48.17

36 38 40 42 44 46 48 50

Niu's method

Proposed method

Imperceptibility comparison - CPSNR (dB)

optimal channel selection

• Combined key

optimal threshold

high quality of watermarked image is obtained

robust against most types of attacks

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UC Lab Kyung Hee University, South Korea 18

UC Lab Kyung Hee University, South Korea 19