ISSN 2319-8885
Vol.04,Issue.08,
April-2015,
Pages:1440-1443
www.ijsetr.com
Reversible Data Hiding by using Optimal Value Data Transfer
VRUSHALI S. PATIL1, MEGHA P. BHALSHANKAR2, MUGDHA A. SONGIRKAR3, SHITAL B. BELDAR4
1
Research Scholar, Dept of Computers, SSBT COET, Bambhori, Jalgaon, MH, India, E-mail: [email protected].
Research Scholar, Dept of Computers, SSBT COET, Bambhori, Jalgaon, MH, India, E-mail: [email protected].
3
Research Scholar, Dept of Computers, SSBT COET, Bambhori, Jalgaon, MH, India, E-mail: [email protected].
4
Research Scholar, Dept of Computers, SSBT COET, Bambhori, Jalgaon, MH, India, E-mail: shitalkumavat @gmail.com.
2
Abstract: We can send the data through the internet accurately and faster to the destination. Also hidden data Invisibility is
very important nowadays. So, in order to transfer the data securely by hidden manner reversible data hiding technique is used.
In reversible data hiding, after the embedded information is extracted the original cover can be losslessely restored. In this
paper using iterative algorithm the optimal rule can be found. The optimal rule can be found under a payload -distortion
criterion. For embedding data the pixel of image can be divided in two sets name set A and set B. The set A and set B contain
odd and even number of pixel respectively. The information that we want to hide can be embedded. Secret data hidden in sets
A and B are concatenated by the receiver to obtain the entire secret data n the information can b extracted in receiver side
efficiently in reverse manner.
Keywords: Reversible Data Hiding; Encrypt Image; Decrypt Image; Data Extraction.
I. INTRODUCTION
In recent years, signal processing in the encrypted domain
has attracted huge research interest. Xinpeng Zhang presented
a unique reversible (lossless) data hiding (embedding)
process, which make able the exact recovery of the original
host with the extraction of the embedded information. And
this exact recovery with lossless data is nothing but the
reversible data hiding. The well-known LSB (least significant
bit) method is used as the data embedding method. Reversible
data hiding is a process that is mainly used for the
authentication of data like images, videos, electronic
documents etc. The chief application of reversible data hiding
technique is in military, medical and law enforcement, IPR
protection and authentication.
II. REVERSIBLE DATA HIDING
A. Reversible Data Hiding Technique
Reversible data hiding is a technique to embed additional
message into some distortion-unacceptable cover media, such
as medical images or military application, with a reversible
manner so that the original cover content can be perfectly
restored after extraction of the hidden message. The general
signal processing typically done before encryption or after
decryption, because As an effective and popular means for
privacy protection, encryption convert ordinary signal into
incomprehensible data. However, in some circumstances that
a content owner does not trust the service provider, the
encrypted data should be manipulate that to keep the plain
content secrete is desired. When the secrete data are
encrypted that to be transmitted, the encrypted data get
compress by a channel provider which does not have any
knowledge of the cryptographic key due to the limited
channel resource. Encryption is an effective means of privacy
protection. To share a secret image with other person, before
transmission a content owner may encrypt the image. In some
cases, a channel administrator needs to add some additional
message within the encrypted image.
The additional message such as the image notation, origin
information, authentication data, within the encrypted image
however he does not know the original image content. It may
be also expected that without any error the original content
can be recovered after decryption and
at receiver side
retrieve of additional message. That means a reversible data
hiding scheme for encrypted image is desirable. Data hiding
is a technique to hide data (representing some information)
into cover media. That is, the data hiding process join two
sets of data, a set of the embedded data and set of the cover
media data. In many cases of data hiding, the cover media
becomes distorted and cannot be inverted back to the original
media due to data hiding. Even after the hidden data have
been removed, the cover media has permanent distortion. In
some applications, e.g. medical diagnosis and law
enforcement it is desired that the original cover media can be
recovered efficiently as before. The marking techniques
fulfill this requirement are called as reversible, lossless,
invertible or distortion-free data hiding techniques.
III. REVERSIBLE DATA HIDING BY USING
OPTIMAL VALUE DATA TRANSFER
In reversible data hiding techniques, the values of sender
image can be modified. According these constraints the
Copyright @ 2015 IJSETR. All rights reserved.
VRUSHALI S. PATIL, MEGHA P. BHALSHANKAR, MUGDHA A. SONGIRKAR, SHITAL B. BELDAR
original content of the image can be correctly restored after
extracting the watermark data on the receiver side. According
to this technique, the optimal constraint of value modification
using a payload-distortion criterion is founded by using the
iterative procedure, and a reversible practical data hiding
scheme was proposed. The secret watermark data, as well as
the additional information used for content recovering, were
carried out by the differences between the original pixelvalues and the corresponding values estimated from the
neighbors. In this, the errors estimated were modified
according to the optimal value transfer rule. Also, the original
image was divided into a number of subsets of the pixel and
the additional information of the subset were always
embedded into the errors estimated in their next subset. The
receiver could successfully extract the content i.e. the
embedded secret data and recover the original content of the
image in the subsets with an inverse order. According to this
technique, a good performance is achieved for the reversible
data hiding.
According to the above scheme, the secret watermark
data, as well as the auxiliary information used for content
recovery, were carried out by the differences between the
original pixel-values and the corresponding values estimated
from the neighbors, the estimation errors are modified
according to the optimal value transfer matrix. The optimal
value transfer matrix is produced for maximizing the amount
of secret data, i.e., the pure payload, by the iterative
procedure described in the previous section. It also stated that
the size of auxiliary information would not affected the
optimality of the transfer matrix. By pixel division in the
original image into two different sets and a number of
different subsets, the embedding of the data is orderly
performed in the subsets, and then the auxiliary information
of the subset is always generated and embedded into the
estimation errors in the next subset. Similarly, the receiver
could successfully extract the embedded secret data and could
recover the original content in the subsets with an inverse
order.
the data hiding key as shown in Fig.1. At the receiver side the
receiver first need to extract the image using the encryption
key in order to extract the data and after that he’ll use data
hiding key to extract the embedded data. It is a serial process
and is not a separable process.
B. Modules Description for Reversible Data Hiding
There are five different types of modules in this project,
these are listed as follows:
Fig.2. Modules of Reversible data Hiding.
1. Data Embedding: Denote the host pixels as where and are
indices of row and column, and divide all pixels into two sets
such as: Set A containing pixels with even and Set B
containing other pixels with odd. So clearly, the four
neighbors of a pixel must be belong to different set as shown
in Fig.2. For each pixel, we may use four neighbors to
estimate its value.
2. Coding Module: We denote matrices and vectors by
boldface fonts and use the same notation for the random
variable and its realization, for simplicity. To do Reversible
Data hiding, a compressible feature sequence should be first
extracted from the original cover. For these schemes, the
features can be usually represented by a binary sequence. So
that, we can directly take the binary feature of the sequence
as the cover to discuss the coding method and follow the
notation established.
3. Recursive Construction: This recursive construction
performs better as compare to the simple method because of
two key points:
 The data can be embedded by an efficient nonreversible
embedding code.
 The cover block is compressed under the condition of the
marked block. However, the recursive construction
cannot approach the upper bound.
Fig.1. Existing System.
IV. THE DESIGN OF HARDWARE
A. Existing System
In existing system reversible data hiding technique the
image is compressed and encrypted by using the encryption
key and the data to hide is embedded in to the image by using
4. Data Extraction: When having an image containing
embedded data, the receiver first divides the image into Set A
and Set B, and then divides Sets A and B into a number of
subsets using the same fashion. Then, extract and AI from the
LSB of the last subset in Set B, and decompose as the weight
values, tand he histogram difference of the first subsets and
the number of iterations. The receiver can be obtain the
estimation error of each pixel in the first subsets with the
weight value, and with the histogram difference and the
iteration number, receiver can use the histogram difference to
International Journal of Scientific Engineering and Technology Research
Volume.04, IssueNo.08, April-2015, Pages: 1440-1443
Reversible Data Hiding by using Optimal Value Data Transfer
retrieve the original scaled histogram and implement the
iterative procedure to retrieve the optimal transfer matrix
used for data-embedding in the first subsets as shown in
Fig.3.
5. Content Recovery: The auxiliary information extracted
from a subset is used to recover the original content of the
previous subset, and then the embedded data in the previous
subset are extracted by using the recovered original
estimation error. That means the original content and the
hidden data in the subsets of Set B, except that last one, can
be recovered and extracted with an inverse order. Then, the
receiver can decomposes the payload hidden in the subsets
into AI of Set A, LSB of Subset of Set B, and the embedded
secret data.
Fig.3. Pixel Dividation.
V. ADVANTAGES AND DISADVANTAGES
Advantages: A smart prediction method is exploited to make
the estimation errors closer to zero, and better performance
can be achieved, but computation complexity will be higher
due to the prediction. The payload-distortion performance
excellent of this proposed scheme. The host image is divided
into number of subsets and the auxiliary information of a
subset is embedded into the estimation errors in the next
subset. By this way, one can successfully extract embedded
secret data and recover the original contents in the subsets
with an inverse order.
Disadvantages: A spare place can always be made available
In these reversible data hiding methods to accommodate
secret data as long as the chosen item is compressible, and the
capacities are not very high. Payload of this method is low
therefore each block can carry one bit.
VI. CONCLUSION
In order carry through a good payload-distortion
performance of reversible data hiding, This work find first the
optimal value transfer matrix by maximizing a target function
of pure payload with an repeating procedure, and then
proposes a practical reversible data hiding scheme. The
differences between the original pixel-values and the
corresponding values calculate approximately from the
neighbors .That are used to carry the payload that is made up
of the real secret data to be embedded and the auxiliary
information for original content recovery. Estimation errors
are modified and the auxiliary information is generated
according to the optimal value transfer matrix. The host
image is separated into a number of subsets and the auxiliary
information of a subset is always embedded into the
calculated errors in the next subset. In this way, one can
successfully extract the embedded secret data and recover the
original content in the subsets with an inverse order. The
payload-distortion performance of the proposed scheme is
very good. For the smooth host images, the proposed scheme
significantly outperforms the previous reversible data hiding
methods. The generated available cover values used the
optimal transfer mechanism which is independent. In other
words, new rule of value modification used the optimal
transfer mechanism and can be used on various cover values.
If a smarter prediction method is shown to make the
estimation errors closer to zero and a good performance can
be achieved, but the computation complexity will be higher
due to the prediction. The combination other kinds of
available cover data and the optimal transfer mechanism used
further study in the future.
VII. FUTURE ENHANCEMENT
We like to propose future enhancement in our reversible
watermarking scheme. Local specifies of the image can be
managed by histogram shifting modulation technique. This
can be apply to image prediction-errors and by using their
neighborhood values, we can apply data in textured areas.
This is not achieved by other methods but histogram shifting
modulation technique can do so. Also, we can select parts of
the image which can be watermarked with the most suitable
reversible modulation by using classification process. The
reference image is used to generate classification, predication
of it, having property of being invariant to the watermark
insertion. Using this method, the watermark embedded and
extractor remain same for message extraction as well as
reconstruction.
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International Journal of Scientific Engineering and Technology Research
Volume.04, IssueNo.08, April-2015, Pages: 1440-1443