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Nov 15, 2014

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VECTORISED AND SCALING APPROACH :FOR HIDING DATA IN IMAGE [STEGANOGRAPHY]

GUIDED BY

: Mr. K.KALIMUTHU

PROJECT MEMBERS : S.GAYATHRI V.MADHAVAN M.UDHAYA MOORTHI N.SHANMUGA SUNDARAM

INTRODUCTION

Steganography is a Greek word derived from steganos,which means Covered and graphia means writing that means covered writing. It is a technique that allows two party to communicate with each other with out knowing to others that the communication is actually taking place. Here secret communication takes place by hiding the data in to a image by encryption and recovering it finally by decryption.

WHY STEGANOGRAPHY?CONFIDENTIALITY [secured Format]

INTEGRITY [data received]

UNREMOVABILITY [ no loss of data]

CRYPTOGRAPHY

yes

no

yes

DIGITAL SIGNATURE

no

yes

no

STEGANOGRAPHY

yes

yes

yes

STEGANOGRAPHY:OVER VIEWCover Image

Message

Stego system Encoder Channel

Key

Estimation of Message

Stego system Decoder

EXISTING SYSTEMSLEAST SIGNIFICANT BITS For hiding the data in to image LSBs are used but the main disadvantage found here is data can be hidden only in the first two bits. WATER MARKING For embedding a source file to an another media watermark embedding was used but the main disadvantage is it will reduce the quality of audio or image at certain level. SPREAD SPECTRUM Here the data is embedded by just expanding the image at the sender side due to this the main disadvantage is noise attack and loss of data at receiver side.

LIMITATIONS OF EXISTING

Not highly securable Data loss Difficult to extract data Cannot Be Rotated Cannot change the position after encryption.

PROPOSED SYSTEM

Embedding- Vector Algorithm. High Security- Quantization. Exhaustive search Technique - pre embedded training sequence For Locking to right shape. Scaling and Rotation - Form the image to actual position

MODULES

Multi scale edge detection Successive Projection Quantization Embedding Data recovery

MULTISCALE EDGE DETECTION

Here in this module all the edges of the image is detected. Edges are detected by spatially correlating the estimated edges across the various scales after decomposing the image by the wavelet transform. To identify the unwanted images wavelet transform is identified as below

Then the convolution process takes place between the filter and the wavelet transform value to avoid the redundancy. Finally with the help of the wavelet maxima found we can identify the right edges as below. if( Wf(u,2j) < Wf(u0,2j))

SUCCESIVE PROJECTION- VECTORISATION ALG

Here the images are just splitted to various parts by vectorisation algorithm. The images divided into various subblocks. we use blocks of size 8 *8. The main purpose of this projection is selecting the initial block of the image. Upper left edge is selected as the initial block. This initial block is selected to identify at receiver side for any rotation operation.

QUANTIZATION

Even and odd quantization are used to represent 0 and 1, respectively. If the projection is quantized to an even number then this block represents 0 and if it is quantized to an odd number then it represents 1. Each block hides one bit in it by projecting it onto certain direction. The receiver performs the same process to recover the hidden information. In particular, each block is projected onto the corresponding subspace and a rounding operation is performed in order to recover the hidden bit.

EMBEDDING

Here we embed the data in to the image which is the main part of steganography. In order to compute the embedded data rate, suppose that the image size is N*N and each 8 * 8 block hides one bit of information. The number of bits that can be hidden = K The size of the Image = N if(K