1. Efficient Image Encoding and Information Embedding Techniques 有效的數位影像編碼與資訊嵌入技術之研究
Advisor: Chang, Chin-Chen
Student: Chen, Chang-Chu
Date: June, 17, 2010
Department of Computer Science and Information Engineering, National Chung Cheng University

2. Outline Part I: VQ encoding technique
Two-Bounds Triangle Inequality for VQ Codebook search
Part II: Information embedding technique
High Capacity SMVQ-based Hiding Scheme Using Adaptive Index

3. Part I: VQ encoding technique

4. Vector quantization “VQ”: Block-based quantizer Applications:
Signal compression (i.e. Image, Speech, …)
Feature recognition
Information security …
一種區塊的量化技術; Feature: face, speech

5. 16 rounds of “-” 15 rounds of “+” 16 rounds of “×”VQ
Euclidean distance
Overview: X i
16 rounds of “-” 15 rounds of “+” 16 rounds of “×”
512
Issue: How to speed up the search?

6. VQ encoding Related works Full-search equivalents
Reduce the range of searching domain
Decrease the online computational operations
Partial-search methods
Organize the codebook by some data structures to label a local search domain

7. Proposed scheme Triangle inequality
Reduce the range of searching domain
Decrease the online computational operations F
: A fixed vector X Ci
Offline computation

8. Experiments (1/2) ms Images Schemes Lena Jet(F16) GoldHill FS 4360
4400
4390
Mielikainen’s scheme
2680
2630
3050
Chang and Lin’s scheme 1
2250
2160
2590
Chang and Lin’s scheme 2
1900
2030
2200
Chang and Lin’s scheme 3
1790
1830
2010
Proposed scheme
1030
890
1130
[31]J. Mielikainen, “A Novel Full-Search Vector Quantization Algorithm Based on The Law of Cosines,” IEEE Signal Processing Letters, vol. 9, no. 6, Jun. 2002, pp
[10]C. C. Chang and I. C. Lin, “Novel Full-Search Schemes for Speeding Up Image Coding Using Vector Quantization,” Real-Time Imaging, vol. 10, no. 2, Apr. 2004, pp

9. Experiments (2/2) ms Codebook sizes Schemes 256 512 1024 FS 4390 8670
16270
Mielikainen’s scheme
3050
5750
10320
Chang and Lin’s scheme 1
2590
4910
9050
Chang and Lin’s scheme 2
2200
4040
7260
Chang and Lin’s scheme 3
2010
3680
6580
Proposed scheme
1130
3840

10. Part II: Information embedding technique
Hiding in VQ and SMVQ index

11. Data hiding Compressed codes: 10111011 11….. 11010110 01…..
Information
(187)10
(214)10
Internet
Sender
Receiver
Information

12. Data hiding in VQ codes (Jo and Kim [27]) 18 Pair 46 46 18 19
[27]M. Jo and H.D. Kim, “A digital image watermarking scheme based on vector quantisation,” IEICE Transactions on Information and Systems, vol.E85-D no.6, Jun. 2002, pp

13. Side Match VQ (SMVQ)
Assumption: Neighboring pixel intensities in an image are pretty similar.
Seed Block
Residual Block
VQ (PSNR=29.11)
SMVQ (PSNR=31.27)
Block artifacts

14. State codebook Codebook (512) State codebook (8)
X = (81, 15, 53, 34, 51,?, ?, ?, 91, ?, ?, ?, 49,?, ?, ?)
Codebook (512)
State codebook (8)

15. Data hiding in SMVQ and VQ codes
Secret message
Compressed code
Residual block
Seed block
SMVQ Embedding
VQ Embedding
> THSMVQ
< THSC
. . . 1 2 3 4 5 6 … 2n
State codebook
Codebook

16. Extracting data Secret message Compressed code Indicator = 1
SMVQ Extracting
VQ Extracting
. . . 1 2 3 4 5 6 … 2n
State codebook
Codebook

17. Experiments(1/3) Methods Images Our method Jo and Kim’s method
Chang and Wu’s method
Secrets
PSNR
Bit Rate
Baboon
22950
23.43
0.177
12372
23.79
0.094
9450
23.76
0.058
Boat
27227
27.35
0.261
13889
27.79
0.106
13978
28.02
0.114
Jet(F16)
29386
28.08
0.305
14273
28.84
0.109
14444
28.93
0.129
Lena
33040
28.80
0.319
14898
29.54
15016
30.13
0.134
Pepper
30327
28.07
0.295
15036
28.71
0.115
14492
28.88
0.127
SailBoat
24710
26.86
0.236
13870
27.46
13787
27.58
[27]M. Jo and H.D. Kim, “A digital image watermarking scheme based on vector quantisation,” IEICE Transactions on Information and Systems, vol.E85-D no.6, Jun. 2002, pp
[12]C. C. Chang and W. C. Wu “A steganographic method for hiding secret data using side match vector quantization”, IEICE Transactions on Information and Systems, vol.E88-D, no.9, Sep. 2005, pp

18. Experiments(2/3)
Host images
Embedded images

19. Experiments(3/3)
The results of different parameters: weight of WSED, THSC , THSMVQ, and the size of the codebook

20. Future Research Directions
Fast VQ codebook search
Find other geometric models or other estimation equations to reduce the range of searching domain and decrease the online computational operations
Data hiding in the compression codes
Investigate other data compression techniques and design the high capacity hiding schemes with reversibility property

21. Conclusions
Part I
Two-Bounds Triangle Inequality for VQ Codebook search
Part II
High Capacity SMVQ-based Hiding Scheme Using Adaptive Index

22. Thanks for your attention