1. Chair Professor Chin-Chen Chang Feng Chia University Jan. 2008
Using Nearest Covering Codes to Embed Secret Information in Grayscale Images
Chair Professor Chin-Chen Chang
Feng Chia University
Jan. 2008

2. Data Hiding Hiding system Stego image Cover image
Secret message

3. Cover Carriers
Image
Video
Sound
Text

4. VQ Encoding Index table Original Image Codebook … (120,155,…,80) 11 2 3 4 5 6 7 8 9 10 11 12 13 14 15
(90,135,…,120)
(100,125,…,150) …
Index table
Original Image
(49,117,…,25)
(50,42,…,98)
(20,65,…,110)
Codebook

5. Previous Work of Steganography on VQ
To find the closest pairs

6. d(CW0, CW8) > TH d(CW13, CW14) > TH Unused CW0, CW8, CW13, CW14

7. Encode Index Table CW0, CW8, CW13, CW14 Unused Index Table
Original Image
Index Table
Unused
CW0,
CW8,
CW13,
CW14

8. A secret message: 1 1 1 1 1 1 1 1
Index Table
Secret bits
CW1, CW2,
CW4, CW5
CW6, CW7
CW11, CW3
CW15, CW10
CW12, CW9 1

9. A secret message: 1 1 1 1 1 1 1 1
Index Table
Secret bits
CW1, CW2,
CW4, CW5
CW6, CW7
CW11, CW3
CW15, CW10
CW12, CW9 1

10. A secret message: 1 1 1 1 1 1 1 1
Index Table
Secret bits

11. (7, 4) Hamming Coding Encoding Data: 1 1 0 12
d1 d2 d3 d4
Data:
Rule: d1  d2  d4  p1 = 0
1  1  1  p1 = 0  p1 = 1
Rule: d1  d3  d4  p2 = 0
1  0  1  p2 = 0  p2 = 0
p1 p2 d1 p3 d2 d3 d4
Encoded data
Rule: d2  d3  d4  p3 = 0
1  0  1  p3 = 0  p3 = 0

12. (7, 4) Hamming Coding (Cont.)
Corrected data:
Error Detection
p1 p2 d1 p3 d2 d3 d4
Correcting
Parity check matrix H:
Received data:
b1 b2 b3 b4 b5 b6 b7
Error bit

13. Inspiration from Hamming Coding
( )T = (000)T  010
( )T = (111)T  710
SECRET
( )T = (110)T  610
( )T = (001)T  110 : : :
( )T = (011)T  310 H :
( )T = (110)T  610
( )T = (111)T  710
( )T = (000)T  010

14. The Proposed Method Pre-process (0000000) : (1111111) C0
( )
( )T = 710 C1 : :
( )T = 610
( ) C3
( )T = 110 : : : : :
( )T = 310
( ) H : : C6
( )
( )T = 610 :
( )T = 710
( )
( )T = 010 : C7
( )

15. The Proposed Method (Cont.)
Embedding 7 10 9 6 3 4 12 8 11 I
( )
Finding a nearest
covering code
( )
( ) : C3
( )
Compute Hamming distance:
( )  ( ) = 4
( )  ( ) = 1
Minimum
( )  ( ) = 2 :

16. The Proposed Method (Cont.)
Embedding
Replace
( )  ( ) = 1 7 10 9 3 4 12 8 11 I’

17. The Proposed Method (Cont.)
Extracting 7 10 9 3 4 12 8 11 I’
0112 H
Secret data

18. Experimental Results Each stego image (512512)
carried 112,347 secret bits
(i.e bpp)

19. Experimental Results (Cont.)

20. Experimental Results (Cont.)

21. Conclusions
The proposed method has a lower cost of chip implementation and saves the power consumption for mobile devices.