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An Iterative Method for Lossless Data Embedding in BMP Images

An Iterative Method for Lossless Data Embedding in BMP Images. Source: Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on Volume 2,  26-28 Nov. 2007 Authors: Jia-Hong Lee a and Mei-Yi Wu b

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An Iterative Method for Lossless Data Embedding in BMP Images

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  1. An Iterative Method for Lossless Data Embedding in BMP Images Source: Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on Volume 2,  26-28 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 barbara@mail.cjcu.edu.tw

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

  3. Abstract • An efficient, simple and highcapacitylossless 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.) N(a)=4 a a a a a a b b N(b)=2 a c c N(c)=3 d(b,c)<th c c b c c b c Overhead+Secret: Secret: 0 0 1 1 1 0 0 Overhead:

  5. Introduction the BMP images 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 AlgorithmEmbedding d a d c b b d d d 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 a a c c e e d 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 AlgorithmEmbedding(cont.) d a d c b b d d d Step3 : compute the minimal overhead O(b) of removing entry b a d a a a a c c d c d e a a a a a a e a a a a a d c b a a c c e e d 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 AlgorithmEmbedding(cont.) Step4 : if N(a)-O(b)>0 then go to Step 5; else go to Step 8 Step5 :Record the overhead O of removing the entry b from the palette. Palette Embedding message: Overhead+M a a b c d e

  9. Proposed AlgorithmEmbedding(cont.) c c c c Step6 : a a c b b b b d d d d d Overhead+M 0 0 1 1 0 1 1 0 Embedding message: a a d a b a a a a a a a a c c d c d e a a a a a a a a a a a a e c c a a a a a a a a a a d c b b a a a a c c c c e e d c b b c c b a a e a a d d d d c b c c c e a a a a a a a a a a c b b e c c e e a a a a a a a a c b b e a a e e d d d a a c

  10. Proposed AlgorithmEmbedding(cont.) Step7 : Copy this modified data to image g. Add a, b to set S and go to step2. d a d c c c d d d a d b a b b c c d c d e a a a a a a Step8 : Output the BMP image g and stop. e a a a a a d c c a a c c e e d 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 AlgorithmExtractioning Step1: d a d c c c d d d 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 c d e a a a a a a e a a a a a d c c a a c c e e d 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 AlgorithmEmbedding(cont.) Step2 :Find all the entry pairs with the same palette color, respectively. Palette a a c d e

  13. a a a a a a a a a a a a a a a a a a a a a a a a a a a a a Proposed AlgorithmExtractioning(cont.) Step3 :assume the entry pair is (a,b) and scan the image data of g d a d c c c d d d a d b b a b b b b c c d d e a a a a a a c 0 0 1 1 0 1 1 0 e a a a a a d c c a a c c e e d 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. a a a a a a a a a a a a a a a a a a a a a a a a a a a a a Proposed AlgorithmExtractioning(cont.) Step4 : d a d c c c d d d a d b a b b c Embedding message:Overhead+M c d d e a a a a a a c e a a a a a d c c 0 0 1 1 0 1 1 0 a a c c e e d 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?

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