A LITERATURE SURVEY ON SECURE JOINT DATA HIDING AND COMPRESSION SCHEME TO STORE HIGH CAPACITY DATA IN IMAGE

International Journal of Technical Research and Applications e-ISSN: 2320-8163,
www.ijtra.com Volume 3, Issue 1 (Jan-Feb 2015), PP. 01-04
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A LITERATURE SURVEY ON SECURE JOINT
DATA HIDING AND COMPRESSION SCHEME TO
STORE HIGH CAPACITY DATA IN IMAGE
Karthiga Gurusamy, V.G.Karthiga1, K.Maheswari2, Dr.S.Kirubakaran3
1
PG Student, INFO Institute of Engineering, Coimbatore
2
Assistant Professor, SNS College of Technology, Coimbatore
3
Assistant Professor, INFO Institute of Engineering, Coimbatore
karthigame2013@gmail.com
Abstract:- This survey propose a Novel Joint Data-Hiding and
Compression Scheme (JDHC) for digital images using side match
vector quantization (SMVQ) and image in painting. In this
JDHC scheme image compression and data hiding scheme are
combined into a single module. On the client side, the data should
be hided and compressed in sub codebook such that remaining
block except left and top most of the image. The data hiding and
compression scheme follows raster scanning order i.e. block by
block on row basis. Vector Quantization used with SMVQ and
Image In painting for complex block to control distortion and
error injection. The receiver side process is based on two
methods. First method divide the received image into series of
blocks the receiver achieve hided data and original image
according to the index value in the segmented block. Second
method use edge based harmonic in painting is used to get
original image if any loss in the image.
I. INTRODUCTION
A. Cryptography
In traditional cryptographic methods [10] [11] encryption
process are used to convert the plaintext into cipher text using
the encryption algorithm. On the other side decryption process
are used to convert the Cipher text into plain text. Cipher text
implies meaningless random data. Even though cryptographic
methods are providing good security, there may be chance of
finding plain text by the attacker. To solve this problem
steganography techniques are developed in both academia and
industry. The goal of cryptography is to make text/information
unreadable by a third party or attacker, whereas the goal of
steganography is to hide the data from a third party or
attacker.
B. Steganography
Steganography[12][13] is the art of hiding information in
other information. Many different carrier file formats like
text/image/audio/video are used but digital images are most
popular because of their usage in the internet. Different
application use different requirements of the Steganography
techniques. Some application requires invisibility of the text
into the carrier image. Some application requires less
visibility. The combined cryptography and steganography
scheme provide high level security to the information. In
recent IT industries facilitates cryptography, stenography and
security issues effectively.
C. Compression
While transferring larger images through standard internet
connection create various scrambling problem. Compression
techniques are incorporated to reduce the image’s file size.
Image compression techniques reduce redundancy and
irrelevance of the image pixels in order to be able to store or
transmit information in an efficient form. Compression
techniques use mathematical calculation to analyze pixel and
reduce pixel resulting in smallest image file size.
Types of Compression:-
Two types of compression techniques are followed
for images.
 Lossy Compression
 Lossless Compression.
Both methods save storage space of the image but they use
different procedures.
a. Lossy Compression
Lossy compression techniques creates smaller image by
discarding excess image pixel from the original image. It
discards details that are too small for the human eye to
differentiate resulting in close approximations of the original
image. An example of an image format that uses this
compression technique is JPEG (Joint Photographic Experts
Group). Lossy methods are works well for natural images such
as photographs where minor/sometimes imperceptible loss of
pixel is acceptable to achieve a substantial reduction in bit
rate. The lossy compression that creates imperceptible
differences may be called visually lossless.
b. Lossless Compression
Lossless compression, never removes any pixel from the
original image, but instead data should be represented in
mathematical formulas. In lossless compression the original
image’s integrity is maintained and the compressed image
output is bit-by-bit identical to the original image input. An
example of an image format that uses this compression
technique is GIF (Graphical Interchange Format). Lossless
compression technique is useful for archival purposes like
medical images, technical drawings, clip arts, or comics.
D. Joint Data Hiding And Compression Scheme (JDHC)
Due to the affect of digital image on the internet,
compressing images and hide the secret data into the
compressed images efficiently deserves in-depth study. The
motivation behind this project is secure image and data by
Novel Joint Data Hiding and Compression to solve issues in
the efficient and effective transmission and storage of
multimedia data. The objective of the proposed scheme is to
hide secret data or images into the host image while
preserving the good image quality of the image. In an open

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network environment is we need to transmit secret or private
data securely. Obviously, the goal of data hiding is to design
schemes with high hiding capacity but low embedding
distortion.
II. EXISTING SYSTEM
Various compression techniques of digital images are
JPEG, JPEG2000, and vector quantization (VQ), SOC with
VQ. In all of these schemes, data hiding is always conducted
after the image compression such that image compression
process and the data hiding process are two separate modules
on the sender/client side. Under this circumstance, the attacker
may have the opportunity to know the compressed image/data.
A. JPEG
JPEG technique controls the level of embedding rate by
using a capacity factor. This method achieves high embedding
capacity of maximum 20% of the compressed image size [1].
B. JPEG 2000
Rate of hiding is very important for efficient and secure
communications. A high-capacity rate steganography scheme
is proposed for the JPEG2000 baseline system by using bit-
plane encoding procedure twice [2].
A steganographic scheme is used to reliably embed high-
volume data into the JPEG2000 bit stream. The upcoming still
image coding standard is an JPEG2000. This new standard
overcomes JPEG by providing several important features such
as resolution/quality progressive image transmission, better
hardness to bit-errors, and Region of Interest (ROI) coding
and so on. So JPEG2000 and its rich features will be used in
many emerging applications [8].
C. Vector Quantization (VQ)
One of the most popular Lossy data compression
algorithms is Vector Quantization(Vector Quantization) .This
process can vary the embedding process according to the
amount of hidden data. In this method, the VQ codebook such
that Left and Top of the image was compressed and remaining
parts are divided into two or more sub code books, and
codebook/sub code books was found to hide secret data. VQ is
widely used for digital image compression due to its simple
use and cost reducing factor in implementation [5].
To improve security in communication Hamming codes
are applied for increasing the embedding efficiency (the
number of bits embedded per embedding change). This
scheme provides increasing steganographic security and good
image quality compared with existing schemes based on VQ
compressed images [9].
D. SOC with VQ
The proposed SOC with VQ scheme, the embedding
process induces no extra coding distortion and adjust the bit
rate according to the size of secret data. It yields a good and
acceptable compression ratio of the image. In next step, the
receiver can efficiently receive both the compressed image
and the embedded data almost at the same time. The search-
order coding (SOC) algorithm was utilized to further compress
the VQ index table and achieve better performance by
searching nearby identical image blocks following a spiral
path[4][5].
E. PROBLEM STATEMENT
 In JPEG method little degradation in image quality
should occur[2].
 JPEG2000 compression standard limited redundancy
and bit stream truncation makes it difficult to hide
information. To overcome these two problems
redundancy evaluation need to use [3].
 Embedding messages into VQ compression codes
may greatly reduce the resolution of image because
compression done at left and top of the image
(Codebook) [5].
 In Vector quantization method Text boundaries are
clear visible between input block.
 The two independent modules data hiding and
compression used in SOC with VQ may cause a
lower efficiency while using in applications [5].
 However, in all of the above mentioned schemes
(JPEG, JPEG 2000, VQ, and SOC WITH VQ) data
hiding could be done after image compression such
that the image compression process and the data
hiding process are two independent modules. So the
attacker may know either image/data [5].
 Security features is not considered in JPEG 2000[8].
III. PROPOSED SYSTEM
The JDHC scheme not only focuses on the high hiding
capacity and recovery quality, also integrates the data hiding
and the image compression into a single module. The survey
of JDHC scheme is based on SMVQ and image in painting
[14][15]. The Side match vector quantization (SMVQ) was
implemented as an advanced version of VQ in which sub
codebooks are used to data hiding and compression [Fig 1.2].
Codebook refers to leftmost column and topmost row
blocks. Sub Codebook refers to blocks excluding leftmost
column and the topmost row. To increase the embedding rate
in SMVQ Weighted Square Euclidean Distance is used. VQ is
also utilized for some complex blocks to control the visual
distortion and error diffusion. Additionally, in decompression
process, the receiver can obtain the hided data/image bits at
any time if he or she preserves the compressed codes. Edge
based harmonic in painting [14][15] are used to construct lost
part of image on receiver side.
Figure. 1.1. Figure. 1.2.
Figure.1.1 Shows Original Image, Figure 1.2 shows output
image get by JDHC Scheme. The Output is based on
combined VQ+SMVQ+Image In painting.

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Architecture of Encryption
(Compression + Data Hiding)
Architecture of Decryption
(Decompression + Data Extraction)
Advantages:-
 For guaranteed communication efficiency and to save
network bandwidth, compression techniques can be
implemented on digital content to reduce redundancy.
 The quality of the decompressed image should be
preserved.
 The data hiding and image compression can be
integrated into one single module; it should avoid
risk of attack from attackers.
 The combined module increase implementation
efficiency.
 SMVQ is developed to alleviate the block artifact of
the decompressed image.
 Increase compression ratio due to the correlation of
the neighboring block is consider and the indices of
the sub codebooks are stored.
 JDHC scheme also be used for the integrity
authentication of the images.
Table 1:-Comparative Study on Existing vs. Proposed System
Methods Existing System Proposed System
Technique VQ (Vector Quantization) [4]. VQ (Vector Quantization)
+SMVQ(Side Match Vector Quantization)
+IMAGE INPAINTING
Compression Done at Codebook (blocks in Left
column and Top most row [5].
Done at Sub code book (blocks Except Left
Column and Top Row)
Compression Name Lossy Compression[4] Lossless Compression
Data Embedding Rate Based on Euclidean distance[4] The Weighted Squared Euclidean distance
(WSED)
Encryption First Image compression could be
done then Data is to be hided as a
separate module [5].
Compression and Data Hiding is a Single
Module
Decryption First Data should be extracted then
Image should be decompressed [5].
Embedded secret bits can be extracted
either before or during the decompression
process

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IV. CONCLUSION
The survey shows that the JDHC scheme based on high
capacity data hiding. On sender side the adopted compression
method switches between SMVQ and image in painting. VQ
is also utilized for some complex blocks to control the visual
distortion and error diffusion. On the receiver side,
decompression for all blocks can also be achieved successfully
by VQ, SMVQ, and image in painting. In JDHC scheme
adjust capacity factor to balance between the image quality
and the embedding capacity. Furthermore, the proposed
method is securer than most of its predecessors. The survey
shows that JDHC scheme has the satisfactory performances
for data hiding rate, compression ratio, and decompression
quality. Furthermore, the JDHC scheme can integrate the two
functions of data hiding and image compression into a single
module seamlessly.
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A LITERATURE SURVEY ON SECURE JOINT DATA HIDING AND COMPRESSION SCHEME TO STORE HIGH CAPACITY DATA IN IMAGE

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