A Review On Modern Secure Mosaic Video Generation For Secure Video Transmission

8/9/2019 A Review On Modern Secure Mosaic Video Generation For Secure Video Transmission

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International Journal of EmergingTrends & Technology in Computer Science(IJETTCS)Web Site: www.ijettcs.org Email: [email protected]

Volume 4, Issue 2, March-April 2015 ISSN 2278-6856

Volume 4, Issue 2, March – April 2015 Page 222

Abstract A new method of combining art image generation and hiding

a secret image into this cubism like image to enhance the

camouflage effect for various information-hiding applications

is proposed. First, a new type of computer art, called line-

based Cubism-like image, which keeps a characteristic of the

cubism art created by extract prominent lines and regions.

For creating the mosaic video we need two video named as

“source” and “target” video files. The first process is picking the target and the source audio for mosaic creation. Picking

of target is similar to that of the selected source video but not

the same. Then converting the lager source video into several

small video for secret purpose. The splitting is used to placed

the source video into target video. after that using the separate

algorithm to find the most similar part of target image for

placing the source tile video. This would be done for all the

split source video. Then we are composing these video in a

mosaic form for hiding the secret information. The mosaic

video is same as that of the target video but this contain the

tile source audio not hear. The output video will send to the

destination, in destination re-mosaic process is held based on

the some algorithm. The tile images are retrieving first for constructing the source image as send by the sender. After

that the tile images are combined to create a original Video

send by the sender.

Keyword: Cubism.LSB,Mosaic etc

I. INTRODUCTIONMosaic is a type of artwork created by composing small

pieces of materials, such as stone, glass, tile, etc. Invented

in ancient time, they are still used in many applications

today. Creation of mosaic images by computer [1] is a new

research direction in recent years.. A good survey under a

unified framework can be found in Battiato et al. [2] in

which a taxonomy of mosaic images into four types is

proposed, including crystallization mosaic, ancientmosaic, photo-mosaic, and puzzle image mosaic. The first

two types are obtained from decomposing a source image

into tiles (with different colors, sizes, and rotations) and

reconstructing the image by properly painting the tiles,

and so they both may be called tile mosaics. The other two

types of mosaics are obtained by fitting images from a

database to cover an assigned source image, and both may

be called multi-picture mosaics. A new type of art image,

called secret-fragment-visible mosaic image, which

contains small fragments of a given source image is

proposed in this study. Observing such a type of mosaic

image, one can see all the fragments of the source image, but the fragments are so tiny in size and so random in

position that the observer cannot figure out what the

source image looks like. Therefore, the source image may

be said to be secretly embedded in the resulting mosaic

image, though the fragment pieces are all visible to the

observer. And this is the reason why the resulting mosaic

image is named secret-fragment-visible. which is the

result of random rearrangement of the fragments of a

secret image in disguise of another image called target

image, creating exactly an effect of image steganography.

The difficulty of hiding a huge volume of image data

behind a cover image is solved automatically by this type

of mosaic image. This is a new technique of information

hiding, not found in the literature so far.

II Literature SurveyIn the proposed system initially the source image is

converted into Cubism-like-art image by extracting

prominent lines and regions. Yi-Zhe Song, Paul L. Rosin,

Peter M. Hall and John Collomosse [3] proposed a method

to simple shapes (e.g. circles, triangles, squares, super

ellipses and so on) are optimally fitted to each region

within a segmented photograph. Stipple Placement using

Distance in a Weighted Graph is proposed by David

Mould [4] provides extra emphasis to image features,

especially edges. Regarding lossless data hiding, several

techniques have been proposed. Xiaomei Quan and

Hongbin Zhang proposed "Lossless Data Hiding Scheme

Based On Lsb Matching [4] deals data hiding based on bit

change. A lossless data hiding method based on histogram

shifting and encryption is proposed by Nutan Palshikar

and Prof. Sanjay Jadhav, and C. Liu in Lossless Data

Hiding using Histogram Modification and Hash

Encryption Scheme [5] . A novel scheme for separable

reversible data hiding in encrypted images developed by

Nutan Palshikar, Prof. Sanjay Jadhav in Separable

Reversible Data Hiding in Encrypted Image [6]. A newsecure image transmission technique which automatically

transforms a given large-volume secret image into a so-

called secret-fragment visible mosaic image of the same

size [7]. A pioneering work done by Wei-Jen Wang,

Cheng-Ta Huang, and Shiuh-Jeng Wang, proposed a

state-of-the-art review and comparison of the different

existing data-hiding methods for VQ-based images in

"VQ Applications in Steganographic Data Hiding Upon

Multimedia Images"[7] and _Real-Time Audio

Watermarking Based on Characteristics of PCM in Digital

Instrument [8] is a work done by Kotaro Yamamoto and

Munetoshi Iwakiri. A lot of research carried out in datahiding inside compressed video in "Data Hiding in Motion

Vectors of Compressed Video Based on Their Associated

Prediction Error" [9] and "Robust Video Data Hiding

A Review On Modern Secure Mosaic Video

Generation For Secure Video Transmission

Mr.Swapnil Patil , Prof.A.A Deshmukh

DEPARTMENT OF ENTC ENGINEERING G. H. Raisoni Institute of Engineering and Technology





Volume 4, Issue 2, March – April 2015 23

Using Forbidden Zone Data Hiding and Selective

Embedding [10].

III RELATED WORKExisting system

In traditional methods secret text can be hidden into

image which is called as Steganography. In this methodonly text data can be encrypted but not image. Secret

images can be hidden using water marking principles.

Water marking is very simple process and it is weak that

anyone can decrypt easily. Mosaic image technique is one

of the efficient techniques to hide the secret images. This

methodology needs another image which is said to be

cover image. Creating mosaic image is also a art of

computer. Many methods have been proposed to create

different types of mosaic images by computer.

Crystallization mosaic, ancient mosaic, photo-mosaic, and

puzzle image mosaic are four types of mosaic images. An

image is fragmented into small tiles. Then these tiles arerandomly embedded onto a cover image. For encryption

embedding process should be performed in some order.

Secret key is used for embedding the small tiles of secret

image onto cover image. LSB (least significant bit)

replacement scheme is a technique mainly used for

embedding process. LSB technique reduces or avoids the

blur effect of encrypted mosaic image.

Existence Architecture

Fig 1 Existence Architecture

Phase 1−creation of a secret-fragment-visible mosaic

image using the tile images of a secret image and the

selected similar target image as input.

Phase 2 −recovery of the secret image from the created

secret-fragment-visible mosaic image. The first phase

includes three stages of operations.

Stage 1.1 −searching a target image most similar to the

secret image.

Stage 1.2 −fitting the tile images in the secret image into

the blocks of the target image.

Stage 1.3 –create a blank image to create a mosaic Image.

Stage 1.4−embedding the tile-image fitting informationinto the mosaic image for later secret image recovery. And

the second phase includes two stages of operations:

Stage 2.1 −retrieving the previously-embedded tile image

fitting information from the mosaic image.

Stage 2.2 −reconstructing the secret image from the

mosaic image using the retrieved information.

Proposed methodology has been divided into 2 phases.

Fig 2 Mosaic Image Creation

Mosaic Image Creation

Fig 1 shows In this first phase, Shamir secret sharing

algorithm is used by which a secret is divided into parts,

giving each participants its own unique part, some of the

parts or all of them are needed in order to reconstruct the

secret counting on all participants to combine together,

the secret might be impractical and therefore sometimes

the threshold scheme is used. Now fitting the tile imagesof the secret image into the target blocks of a preselected

target image. After this transforming the color

characteristic of each tile image in the secret image to

become that of the corresponding target block in the target

image and rotating each tile image into a direction with

the minimum RMSE value with respect to its

corresponding target block. After the rotation embedding

relevant information into the created mosaic image for

future recovery of the secret image. In this way we get the

output secret fragment visible mosaic image.

Secret Image Recovery

In this second phase, extracting the embedded information

for secret image recovery from the mosaic image, and

recovering the secret image using the extracted

information by secret image recovery algorithm. In this

phase result

will be calculated and optimize if required result is in the

form of delay and accuracy

Fig 1 Main Module at sender and Receiver






There are two major stages in the proposed Image

Stenographic Technique

1 Sender Side

2 Receiver Side

At sender side a new type of computer art, called line-

based Cubism-like image, which keeps a characteristic of

the Cubism art created by extract prominent lines and

regions. Then the cubism like image is divided into target

tiles and the secret is also divided into secret tiles of same

size as target. A mapping sequence is created based on

secret-target tile similarity and the secret image is

embedded into the target using that mapping sequence. To

enhance security a secret key is shared between sender and

receiver. The secret key will generate a random

permutation that is used to permuting the mapping

sequence. That mapping information is also embedded

into the Cubism Image. Finally a secret-embedded-

mosaic-image is created as steno image and that is sent to

the receiver. At the receiver side when the receiver gets

the output image, using the common secret key, he

retrieves the mapping sequence and using that mapping

sequence he will extract the secret image from the cubism

image.

Basic Idea of Secret Fragment Visible Mosaic Image

The formation of mosaic image which visually

approximates the target image using the tiles or blocks

from the secret image and the recovery of secret image

from the encrypted mosaic image has the following basicsteps

1. Construction of a color image database for use in

selecting similar target images for given secret image

2. Creation of a secret-fragment-visible mosaic image

using the tile images of a secret image and the selected

similar target image as input

3. Recovery of the secret image from the created secret

fragment- visible mosaic image The first step includes

selection of a wide variety of images and also calculation

of some image similarity measures and histogram. The

second step includes

1. Searching the database for a target image the mostsimilar to the secret image

2. Fitting the tile images in the secret image into the

blocks of the target image to create a mosaic image

3. Embedding the tile-image fitting information into the

mosaic image for later secret image recovery

The third step corresponds to the decryption. It has the

following steps

1. Retrieving the previously-embedded tile-image

fitting information from the mosaic image

2. Reconstructing the secret image from the mosaic image

using the retrieved information

Fig 3 Proposed Work

The existing work proposes a methodology of generating

image mosaics. Our image mosaic generating system

divides an input image into many tiles; and then for each

tile, it fetches the image with the most similar content

from an image database and replaces the tile with the

image.

Steps

Phase 1−creation of a secret-fragment-visible mosaicaudio using the tile audio of a secret audio and the

selected similar target audio as input.

Phase 2 −recovery of the secret image from the created

secret-fragment-visible mosaic audio. The first phase

includes three stages of operations.

Stage 1.1 −searching a target audio most similar to the

secret audio.

Stage 1.2 −fitting the tile audio in the secret image into

the blocks of the target audio.

Stage 1.3 –create a blank audio to create a mosaic audio.

Stage 1.4−embedding the tile-image fitting information

into the mosaic audio for later secret audio recovery. Andthe second phase includes two stages of operations:

Stage 2.1 −retrieving the previously-embedded tile audio

fitting information from the mosaic audio.

Stage 2.2 −reconstructing the secret audio from the

mosaic audio using the retrieved information.

Fig 3 shows proposed a new type of art work can be used

for secure keeping or covert communication of secret

audio. This type of mosaic image is composed of small

fragments of an input secret audio; and though all the

fragments of the secret audio can be hear clearly, they are

so tiny in size and so random in position that people

cannot figure out what the source secret audio looks like.

For creating the mosaic audio we need two audio named

as “source” and “target” audio files. The first process is

picking the target and the source audio for mosaic

creation. Picking of target audio is similar to that of the






selected source audio but not the same. Then converting

the lager source audio into several small audio for secret

purpose. The splitting is used to placed the source audio

into target audio, and doesn’t play to the users. After that

using the separate algorithm to find the most similar part

of target image for placing the source tile audio. Thiswould be done for all the split source audio.

Then we are composing these audio in a mosaic form for

hiding the secret information. The mosaic audio is same

as that of the target audio but this contain the tile source

audio not hear. The output audio will send to the

destination, in destination re-mosaic process is held based

on the some algorithm. The tile images are retrieving first

for constructing the source image as send by the sender.

After that the tile images are combined to create a original

audio send by the sender. The other people can’t hear the

audio without having the mosaic reconstructing algorithm.

The re-mosaic process is done by reverse process of the

mosaic process.

Algorithm

Algorithm 1 Mosaic image creation

Input: a secret image S, a target image T, and a secret key

K.

Output: a secret-fragment-visible mosaic image F.

Steps:

Stage 1. fitting the tile images into the target blocks.

Step 1. If the size of the target image T is different from

that of the secret image S, change the size of T to be

identical to that of S; and divide the secret image S into n

tile images {T1, T2, . . . , Tn} as well as the target image

T into n target blocks {B1, B2, . . . , Bn} with each Ti orBi being of size NT .

Step 2. Compute the means and the standard deviations of

each tile image Ti and each target block Bj for the three

color channels according to (1) and (2); and compute

accordingly the average standard deviations for Ti and Bj ,

respectively, for i = 1 through n and j = 1 through n.

Step 3. Sort the tile images in the set Stile = {T1, T2, . . .

, Tn} and the target blocks in the set Starget = {B1, B2, . .

. , Bn} according to the computed average standard

deviation values of the blocks; map in order the blocks in

the sorted Stile to those in the sorted Starget in a 1-to-1

manner; and reorder the mappings according to theindices of the tile images, resulting in a mapping sequence

L of the form: T1 → Bj1 , T2 → Bj2 , . . . , Tn → Bjn .

Step 4. Create a mosaic image F by fitting the tile images

into the corresponding target blocks according to L.

Stage 2. performing color conversions between the tile

images and the target blocks.

Step 5. Create a counting table TB with 256 entries, each

with an index corresponding to a residual value, and

assign an initial value of zero to each entry (note that each

residual value will be in the range of 0 to 255).

Step 6. For each mapping Ti →Bji in sequence L,

represent the means μc and μ _ c of Ti and Bji,

respectively, by eight bits; and represent the standard

deviation quotient qc appearing in (3) by seven bits,

according to the scheme described in Section III(A) where

c = r, g, or b.

Step 7. For each pixel pi in each tile image Ti of mosaic

image F with color value ci where c = r, g, or b, transform

ci into a new value c__i by (3); if c__i is not smaller than

255 or if it is not larger than 0, then change c__i to be 255

or 0, respectively; compute a residual value Ri for pixel pi

by the way described in Section III(C); and increment by 1the count in the entry in the counting table TB whose

index is identical to Ri.

Stage 3. rotating the tile images.

Step 8. Compute the RMSE values of each color

transformed tile image Ti in F with respect to its

corresponding target block Bji after rotating Ti into each

of the directions θ =0o, 90o, 180o and 270o; and rotate Ti

into the optimal direction θo with the smallest RMSE

value.

Stage 4. embedding the secret image recovery

information.

Step 9. Construct a Huffman table HT using the content of

the counting table TB to encode all the residual values

computed previously.

Step 10. For each tile image Ti in mosaic image F,

construct a bit stream Mi for recovering Ti in the way as

described in Section III(D), including the bit-segments

which encode the data items of: 1) the index of the

corresponding target block Bji; 2) the optimal

rotation angle θ° of Ti; 3) the means of Ti and Bji and the

related standard deviation quotients of all three color

channels; and 4) the bit sequence for

overflows/underflows with residuals in Ti encoded by the

Huffman table HT constructed in Step 9.

Step 11. Concatenate the bit streams Mi of all Ti in F in araster-scan order to form a total bit stream Mt ; use the

secret key K to encrypt Mt into another bit stream M_t ;

and embed M_

t into F by the reversible contrast mapping scheme

proposed in [24].

Step 12. Construct a bit stream I including: 1) the number

of conducted iterations Ni for embedding M_ t; 2) the

number of pixel pairs Npair used in the last iteration; and

3) the Huffman table HT constructed for the residuals; and

embed the bit stream I into mosaic image F by the same

scheme used in Step 11.

Algorithm 2 Secret image recoveryInput: a mosaic image F with n tile images

{T1, T2, . . . ,Tn} and the secret key K.

Output: the secret image S.

Steps:

Stage 1. extracting the secret image recovery

information.

Step 1. Extract from F the bit stream I by a reverse

version of the scheme proposed in [24] and decode them

to obtain the following data items: 1) the number of

iterations Ni for embedding M_ t ; 2) the total number of

used pixel pairs Npair in the last iteration; and 3) the

Huffman table HT for encoding the values of the residuals

of the overflows or underflows.

Step 2. Extract the bit stream M_t using the values of Ni

and Npair by the same scheme used in the last step.

Step 3. Decrypt the bit stream M_t into Mt by K.






Step 4. Decompose Mt into n bit streams M1 through Mn

for the n to-be-constructed tile images T1 through Tn in S,

respectively.

Step 5. Decode Mi for each tile image Ti to obtain the

following data items: 1) the index ji of the block Bji in F

corresponding to Ti; 2) the optimal rotation angle θ° ofTi; 3) the means of Ti and Bji and the related standard

deviation quotients of all color channels; and 4) the

overflow/underflow residual values in Ti decoded by the

Huffman table HT.

Stage 2. recovering the secret image.

Step 6. Recover one by one in a raster-scan order the tile

images Ti, i = 1 through n, of the desired secret image S

by the following steps: 1) rotate in the reverse direction

the block indexed by ji, namely Bji, in F through the

optimal angle θ° and fit the resulting block content into Ti

to form an initial tile image Ti; 2) use the extracted means

and related standard deviation quotients to recover the

original pixel values in Ti according to (4); 3) use the

extracted means, standard deviation quotients, and

(5) to compute the two parameters cS and cL; 4) scan Ti

to find out pixels with values 255 or 0 which indicate that

overflows or underflows, respectively, have occurred

there; 5) add respectively the values cS or cL to the

corresponding residual values of the found pixels; and 6)

take the results as the final pixel values, resulting in a

final tile image Ti.

Step 7. Compose all the final tile images to form the

desired

secret image S as output.

4.ConclusionThe proposed work which can be used for secure keeping

or covert communication of secret audio. This type of

mosaic audio is composed of small fragments of an input

secret image and though all the fragments of the secret

audio can be seen clearly, they are so tiny in size and so

random in position that people cannot hear out what the

source secret audio looks like. A novel algorithm has also

been proposed for searching the tile audio in a secret

audio for the most similar ones to fit the target blocks of a

selected target audio more efficiently..

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A Review On Modern Secure Mosaic Video Generation For Secure Video Transmission

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