multimedia network security lab. on stut adaptive weighting color palette image speaker:jiin-chiou...

Multimedia Network Security Lab. On STUT

Adaptive Weighting Color Palette Image

Speaker:Jiin-Chiou Cheng

Date:99/12/16

Multimedia Network Security Lab. On STUT2

Outline

• Introduction• Relative works• Proposed scheme• Diagram• Experimental results• Discussion

Multimedia Network Security Lab. On STUT3

Introduction

• Recently, researchers pay more attention to consider how to provide the photo’s safety and copyright.

• In the paper, we let distinct color palette to be embedded in cover-image according to user’s authority. The user will recover the cover image more clearly with high authority.

• Besides, we provide a adaptive data hiding scheme to embed the color palette into cover-image.


Relative works

• Chaumont-Puech’s scheme

Chaumont M. and Puech W., “A Color Image Hidden in a Grey-Level Image,” in ISandT Third European Conference on Colour in Graphics, Imaging, and Vision, CGIV’2006, pp. 226–231. , 2006.

• Ni Z. et al. reversible data hiding scheme

Ni Z., Shi Y. Q., Ansari N., and Su W. “Reversible Data Hiding,” IEEE Trans. on Circuits and System for Video Technology, Vol.16, pp.345-362, 2006.

4


Relative works -- Chaumont-Puech’s scheme

Input: The color image as cover-image.

Output: The stego-image.

(1). Find out the non-repeat pixels in the color image.

(2). Use the ISO-DATA K-means [1] algorithm to get K pixels for color representation. The training formula is following:

where I is a color image of dimension N pixels, C(k) is the kth color of the research K colors, dist is a distance function to calculate the Euclidean distance between I and C(k), and Pı,k {0,1} is the membership value of pixel ı to color k.

(3). Use Layer Running [4-6] algorithm to get new reordering palette and new index grayscale image.

(4). Embed the color image’s palette information into the grayscale image’s LSB.

5

N

l

K

kkl

kCPkl kClIdistPkCP

kl 1 1

2,

)(,, ))(),((minarg)(,

,


Relative works -- Ni Z. et al. reversible data hiding scheme

Input: Cover-image

Output: Stego-image

(1). Find out the peak point (pixel value is 2) and the zero point (pixel value is 6) shown as Fig.(a).

(2). The value of pixels between 3 and 5 is incremented by “1”, i.e., shifting the range of the histogram, [3 5] to the right-hand side by 1 unit and leaving the grayscale value 3 empty shown as Fig.(b).

(3). Embed the secret data “0” and “1” into the grayscale value of 2 and 3, respectively. The stego-image’s histogram is shown as Fig.(c).

6(a) (b) (c)


Proposed scheme

I. Color Palette Setup Phase

II. Priority Weighting Distribution Phase

III. Color Palette Embedding Phase

IV. Extracting Secret Data Phase

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I. Color Palette Setup Phase (LBG[8] method)

Input: Cover-image

Output: Color palette with n colors

(1). Generate a palette from the cover-image.

where x(n) is the non-repeat color pixel in cover-image, and we randomly select y(i), i= from x(n), .

(2). Group training by using

where d(p,q) is the Euclidean distance between pixel p and pixel q and h ≠ i.

(3). If the palette is different from previous palette, then go to (4). Otherwise, stop the phase.

(4). Update the initial pixel by

where G(i) is the ith group number. Go to (2).8

},....,1|)({

},...,1|)({

cNiiyC

Mjjx

　

))}(),(())(),(({)( hyjxdiyjxdiG

)()(

)()(

1 )(

jGjx

jxiG

iy


II. Priority Weighting Distribution Phase

Input: 256 color palette A and 512 color palette B.

Output: High Priority and Low Priority palettes.

(1). Compute the Euclidean distance between palette A and B for every pixel. the high priority palette is found out the 256 shortest Euclidean distances from palette B.

(2). After comparing with palette A, the high priority palette is found out the 256 shortest Euclidean distances from palette B.

(3). The other 256 pixels in palette B are distributed to low priority palette.

9


III. Color Palette Embedding Phase

Input: Cover image and color palette.

Output: Stego-image.

(1). Compute the difference value between the neighbor pixels.

(2). Statistical the difference number by using the histogram.

(3). Find out the peak-point and zero-point.

(4). Translate the pixel value in color palette into binary data.

(5). Using the NSAS method to embed these secret data.

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IV. Extracting Secret Data Phase

Input: Stego-image.

Output: The original image.

(1). Compute the difference value between the neighbor pixels.

(2). Find the histogram of the stego-image.

(3). Scan the histogram from left to right and compute the 4 continuous difference values by using the following equations

where yi, yi+1, yi+2, and yi+3 are the numbers of 4 continuous difference value from the ith value. and represent the boundary values, their values are depended on the ratio of the number of bit 0 and bit 1 in the input secret data.

(4). If the result such that the boundary condition and then we can find out the secret data is embedded between the middle of 4 continuous differences value. Otherwise, repeat (3) until the whole histogram is scanned completly.11

13

231

i

ii

i

ii

y

yy

y

yy2

1

21

i

ii

y

yy

1 2

12

Cover image Index image

Palette with 512 colors

High Priority Palette A with 256 colors

Low Priority Palette B with 256 colors

Embedding procedure

By LBG method

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Low Priority Palette B with 256 colors

Index image

Index image

Embedded adaptively in thehistogram of different valueof index image.[ similar to NSAS method]

Stego index imagewith high quality

Stego index imagewith low quality

Embedding procedure

Embedded adaptively in thehistogram of different valueof index image.[ similar to NSAS method]

different value

# #

different value

#

different value

0 1

1

0 1

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Extracting procedure

Stego index imagewith high quality

#

different value

4

34

2

21

y

yy

y

yy


Index image

Recovered cover image with high quality

y1 y2 y3 y4

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Experimental result

Figure 6(a) Recovered cover image with high quality

Figure 6(b) Recovered cover image with low quality

Table 1. Recovered image’s quality with different priority for 512 color palette.


Q & A

Thanks for listening

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