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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
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Outline Abstract Introduction the BMP images Proposed Algorithm
Experimental Results Conclusions
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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
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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:
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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.
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Proposed Algorithm Embedding
c 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
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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
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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
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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
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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
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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
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Proposed Algorithm Embedding(cont.)
Step2 :Find all the entry pairs with the same palette color, respectively. Palette a a c d e
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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
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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
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Results
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Conclusion An efficient, simple and highcapacity
lossless embedding method for 256 color grayscale BMP images is presented. How to find the pair?
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