data hiding technique using entropy calculation and image

DATA HIDING TECHNIQUE USING ENTROPY CALCULATION AND IMAGE COMPRESSION

USING BTC

BYSHASHIVARDHAN N.A

1ST SEM M.TechD.E.C.S

OVERVIEWINTRODUCTION

STEPS INVOLVED

BLOCK TRUNCATION CODING

EMBEDDING ALGORITHM

EXTRACTION ALGORITHM

APPLICATIONS

CONCLUSION

BIBLIOGRAPHY

DATA HIDING TECHNIQUE USING ENTROPY CALCULATION AND IMAGE COMPRESSION USING BTC

OBJECTIVE:

To provide a secure data hiding technique using information theory and also generate random distribution of message image over the cover image and also compress the message using block truncation coding and recover it at high quality.


STEPS INVOLVED…………

Message image compression using block truncation coding (BTC)

Embedding the message image into the cover image.

Extracting message image from cover image.


COVER IMAGE EMBEDDING

KEY

STEGO IMAGE

MESSAGE

MESSAGE EXTRACTING

KEY


The block truncation coding involves the following steps: An image is divided into non-overlapping blocks. The size of a block

could be (4 × 4) or (8 × 8) , etc (here we will use (4 × 4) blocks). Calculate the average gray level of the block. For (4 × 4) block:

m =1/16 ΣΣx(i,j) , x (i, j) represents pixels in the block.

Pixels in the image block is then classified into two kinds first: with their gray level is greater than block average gray level and

Second: with their gray level is lower than or equal block average gray level. The average gray level of this two kind of pixels are calculated:

Where K is the number of pixels whose gray level is greater than m.


BTC CONTD……

A binary block, denoted b, is also needed to classify the pixels. We can use “1” to represent a pixel whose gray level is greater than m and “0” to represent a pixel whose gray level is less than or equal to m.

In the encoder an image block is constructed by replacing with “1’s” and with “0’s”.


BTC CONTD……

THE ORIGINAL IMAGE BLOCK. THE ENCODED BINARY BLOCK

THE AVERAGE GRAY LEVEL=159

THE RECONSTRUCTED IMAGE

BLOCK BY THE DECODER


EMBEDDING ALGORITHM:

“ This algorithm takes cover, message images and a key as an input and produces a stego image”.

Cover image

Hiding system

Secret image

Secret key

Stego image

EMBEDDING ALGORITHM

.



MSB LSB

8 7 6 5 4 3 2 1

LSB: Least significant bit

8 bits/pixelExample:

1 0 0 0 0 0 0 0 =128

1 0 0 0 0 1 1 1 =135

Original pixel value

Processed pixel value

Similar

color

BLOCK DIAGRAM

Secret image

Hiding system

Cover image

Cover image

Stego image

Secret key

extraction


EXTRACTION: The extraction algorithm reverse the operation of

embedding algorithm, using key and entropy calculation to determine the amount of data embedded in each pixel and recover it to construct the message again from cover.

First divide the stego-image into blocks and do the following: calculate the entropy of the’4’ most significant bits. If it is

greater than ‘2’ then recover ‘4’ bits from 4 least significant bits if not calculate the entropy of ‘5’ most significant bits if it is greater than’2’ then recover ‘3’ bits from ‘3’ least significant bits if not then recover ‘2’ bits from ‘2’ least significant bits.

After recovering the different bits decode it again by using the BTC algorithm and reconstruct the message image.


APPLICATIONS:

SECRET COMMUNICATION:- in military issues, trade secret ,blue print or other sensitive information can be transmitted without alerting the hackers.

COPYRIGHT PROTECTION:- A secret copyright notice or watermark can be embedded inside an image to identify it as intellectual property. In addition ,when an image is sold or distributed an identification of the recipient and time stamp can be embedded to identify potential pirates.


CONCLUSION AND SCOPE FOR FUTURE WORK:-

This paper provides a secure data hiding technique using information theory and also generate random distribution of message image over the cover image and also compress the message using block truncation coding and recover it at high quality.It also provides large data embedding without making noticeable distortion.

FUTURE WORK:-Hiding not only images but extending it to audio, text formats, etc.

REFERENCES

Secure Perceptual Data Hiding Technique using Information Theory, Mohiy M. Hadhoud, Nabil A. Ismail, Shawky El-kelany, ICEEC’04, Faculty of Engineering- Ain Shams University, Cairo, Egypt, September 2004.

An Entropy Based Technology for Information Embedding In Images, Marc Van Droogenbroeck and Jerome Delvaux , Institute Montefiore B-28 , Department of Electrical and Computer Science.

Information Hiding – A Survey ,Febien A. P. ,Ross Anderson and Markus G. Kuhn, Proceeding of the IEEE, special issue on protection of multimedia content,87(7):1062 - 1078,july 1999.

Applications for Data Hiding , W. Bender , W. Butera , D. Gruhi , R. Hwang , F. J. Paiz , S. Pogreb , IBM System Journal , VOL 39 ,NOS 3&4 ,2000.

data hiding technique using entropy calculation and image

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