1. An Iterative Method for Lossless Data Embedding in BMP Images
Source: Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP Third International Conference on Volume 2,  Nov. 2007
Authors: Jia-Hong Lee a and Mei-Yi Wu b
a Department of Information Management, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan
b Department of Information Management, Chang Jung University, Tainan, Taiwan

2. Outline Abstract Introduction the BMP images Proposed Algorithm
Experimental Results
Conclusions

3. Abstract
An efficient, simple and highcapacity lossless embedding method for 256-color grayscale BMP images
A color palette which is a great location to embed a large amount of data.
Computation the color of occurrence frequency
Palette modification scheme

4. Abstract(cont.) a a b b a a a a a c c c c c b c b c N(a)=4 N(b)=2
N(c)=3
d(b,c)<th c c c b c b c
Overhead+Secret:
Secret: 1 1 1
Overhead:

5. Introduction the BMP images
bitmap header
bitmap information
color palette
bitmap data
bitmap header: stores general information about the bitmap file.
bitmap information :stores detailed information about the bitmap image.
color palette
0,0,0,0
0,0,255,0
color palette :stores the definition of the colors being used for indexed color bitmaps.
bitmap data :stores the actual image, pixel by pixel.

6. Proposed Algorithm Embeddingc b b
BMP image :f
Hidden message :M
Threshold :th
Set S=Φ
Step2:
Step1: a d a a a a c c d
Compute the occurrence frequency N(i) for
image f, where i ！ЕS .
N(a)= 32
N(b)= 7
N(c)= 13
N(d)= 17
N(e)= 12 c d e a a a a a a e a a a a a d c b c c e e a d a c b b a e a d d d d c c e a a a a a c b e e e a a a a c b e a e e d d d a c

7. Proposed Algorithm Embedding(cont.)
Step3 : compute the minimal overhead O(b) of removing entry b a d a a a a c c d d e a a a a a a c e a a a a a d c b c c e e a d a c b b a e a d d d d c
O(b) c e a a a a a c b
D(b,c)<th ,where b！Е S
and c ！Е S e e e a a a a c b e a e e d d d a c

8. Proposed Algorithm Embedding(cont.)
Step5 :Record the overhead O of removing the entry b
from the palette.
Step4 : if N(a)-O(b)>0 then go to Step 5; else go to Step 8
Palette
Embedding message: Overhead+M a b a c d e

9. Proposed Algorithm Embedding(cont.)
Step6 : d d a a d d d c b b b b
Overhead+M
Embedding message: 1 1 1 1 a a d a a b a a a a a a a c c d d e a a a a a a a a a a a a c e a a a a a a a a a a d c c b c b c c e e a a d a a c c c b b b c c b a a e a a d d d d c c e a a a a a a a a a a c c c b b e e e a a a a a a a a c c c b b e a a e e d d d a a c

10. Proposed Algorithm Embedding(cont.)
Step7 : Copy this modified data to image g. Add a, b to
set S and go to step2. d a d d d c c c a d b a b b c c d d e a a a a a a c
Step8 : Output the BMP image g and stop. e a a a a a d c c c c e e a d a c c c a e a d d d d c c e a a a a a c c e e e a a a a c c e a e e d d d a c

11. Proposed Algorithm Extractioning
Step1: d d d c c c
BMP image :g a d b a b b c c d
Compute the occurrence frequency N(i) for
image f, where i ！ЕS .
N(a)= 29
N(b)= 3
N(c)= 20
N(d)= 17
N(e)= 12 d e a a a a a a c e a a a a a d c c c c e e a d a c c c a e a d d d d c c e a a a a a c c e e e a a a a c c e a e e d d d a c

12. Proposed Algorithm Embedding(cont.)
Step2 :Find all the entry pairs with the same palette
color, respectively.
Palette a a c d e

13. Proposed Algorithm Extractioning(cont.)
Step3 :assume the entry pair is (a,b) and scan the image data of g d a d a d d d c c c a d b b a b b b b c d c d e a a a a a a c 1 1 1 1 e a a a a a d c c c c e e a d a c c c a e a d d d d c c e a a a a a c c e e e a a a a c c e a e e d d d a c

14. Proposed Algorithm Extractioning(cont.)
Step4 : d a d a d d d c c c a d b a b b c d c
Embedding message: Overhead+M d e a a a a a a c e a a a a a d c c 1 1 1 1 c c e e a d a c c c a e a d d d d c c e a a a a a c c e e e a a a a c c e a e e d d d a c

15. Results

16. Conclusion An efficient, simple and highcapacity
lossless embedding method for 256 color grayscale BMP images is presented.
How to find the pair?