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Reversible Data Hiding By Using Optimal Value Data Transfer
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Vrushali S. Patil , 2Megha P.Bhalshankar, 3Mugdha A. Songirkar, 4Shital B. Beldar.
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B.E. Student of Computer Dept., SSBT COET, Bambhori, Jalgaon, MH-India,vrushalip113@gmail.com
B.E. Student of Computer Dept., SSBT COET, Bambhori, Jalgaon, MH-India,meghab1718@gmail.com
3B.E. Student of Computer Dept., SSBT COET, Bambhori, Jalgaon, MH-India, mugdhas_m@rediffmail.com
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B.E. Student of Computer Dept., SSBT COET, Bambhori, Jalgaon, MH-India, shitalkumavat @gmail.com
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Abstract—
data hiding technique is in military, medical and law
accurately and faster to the destination. Also hidden data
enforcement, IPR protection and authentication.
We can send the data through the internet
Invisibility is very important nowadays.
So, in order to
transfer the data securely by hidden manner reversible data
II. Reversible Data Hiding
hiding technique is used. In reversible data hiding, after the
A. Reversible Data Hiding Technique
, 2M. Name
embedded
information is extracted the original cover can be
of JNTU, Hyderabad, AP-India,ramesda@gmail.com
losslessely
restored. In AP-India
this paper using iterative algorithm
JNTU, Hyderabad,
M.Tech
Student
Reversible data hiding is a technique
to embed
additional
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the optimal rule can be found. The optimal rule can be
such as medical images or military application, with a
found under a payload -distortion criterion. For embedding
reversible manner so that the original cover content can be
data the pixel of image can be divided in two sets name set
perfectly restored after extraction of the hidden message.The
A and set B. The set A and set B contain odd and even
general signal processing typically done before encryption
number of pixel respectively. The information that we want
or after decryption, because As an effective and popular
to hide can be embedded. Secret data hidden in sets A and
means for privacy protection, encryption convert ordinary
B are concatenated by the receiver to obtain the entire secret
signal into incomprehensible data. However, in some
data n the information can b extracted in receiver side
circumstances that a content owner does not trust the service
efficiently in reverse manner.
provider, the encrypted data should be manipulate that to
Index Terms-- Reversible data hiding; Encrypt image; Decrypt
keep the plain content secrete is desired.When the secrete
image; Data extraction.
data are encrypted that to be transmitted, the encrypted data
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HOD, ECE Dept,
message into some distortion-unacceptable cover media,
get compress by a channel provider which does not have any
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
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.
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Data hiding is a technique to hide data (representing
corresponding values estimated from the neighbors,
some information) into cover media. That is, the data
estimation errors are modified according to the optimal
hiding process join two sets of data, a set of the embedded
value transfer matrix. The optimal value transfer matrix is
data and set of the cover media data. In many cases of
produced for maximizing the amount of secret data, i.e., the
data hiding, the cover media becomes distorted
and
pure payload, by the iterative procedure described in the
cannot be inverted back to the original media due to data
previous section. It also stated that the size of auxiliary
hiding. Even after the hidden data have been removed ,the
information would not affected the optimality of the transfer
cover
some
matrix. By pixel division in the original image into two
applications, e.g. medical diagnosis and law enforcement
different sets and a number of different subsets, the
it is desired that the original cover media can be
embedding of the data is orderly performed in the subsets,
recovered efficiently as before.The marking techniques
and then the auxiliary information of the subset is always
fulfill this requirement are called as reversible, lossless,
generated and embedded into the estimation errors in the
invertible or distortion-free data hiding techniques .
next subset. Similarly, the receiver could successfully
media
has
permanent
distortion.
In
III. Reversible Data Hiding By using Optimal value
Data transfer
the
extract the embedded secret data and could recover the
original content in the subsets with an inverse order.
In reversible data hiding techniques, the values of sender
image can be modified. According this constraints the
IV. THE DESIGN OF HARDWARE
original content of the image can be correctly restored after
A. Existing System
extracting the watermark data on the receiver side.
In existing system reversible data hiding technique the
According to this technique, the optimal constraint of value
image is compressed and encrypted by using the encryption
modification using a payload-distortion criterion is founded
key and the data to hide is embedded in to the image by
by using the iterative procedure, and an reversible practical
using the data hiding key. At the receiver side the receiver
data hiding scheme was proposed. The secret watermar
first need to extract the image using the encryption key in
kdata, as well as the additional information used for content
order to extract the data and after that he’ll use data hiding
recovering, were carried out by the differences between the
key to extract the embedded data. It is a serial process and is
original pixel-values and the corresponding values estimated
not a separable process.
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
Figure 1. Existing System
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1) The data can be embedded by an efficient nonreversible
B. Modules Description For Reversible Data Hiding
embedding code.
There are five different types of modules in this project,
2) the cover block is compressed under the condition of the
these are listed as follows:
marked block. However, the recursive construction cannot
approach the upper bound
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 retrieve the original
Figure 2. Modules of Reversible data Hiding
scaled histogram and implement the iterative procedure to
retrieve the optimal transfer matrix used for data-embedding
1. Data Embedding
in the first subsets.
Denote the host pixels as where and are indices of row and
5. Content Recovery
column, and divide all pixels into two sets such as: Set A
The auxiliary information extracted from a subset is used to
containing pixels with even and Set B containing other
recover the original content of the previous subset, and then
pixels with odd. So clearly, the four neighbors of a pixel
the embedded data in the previous subset are extracted by
must be belong to different set. For each pixel, we may use
using the recovered original estimation error. That means
four neighbors to estimate its value.
the original content and the hidden data in the subsets of Set
2. Coding Module
B, except that last one, can be recovered and extracted with
We denote matrices and vectors by boldface fonts and use
an inverse order. Then, the receiver can decomposes the
the same notation for the random variable and its realization,
payload hidden in the subsets into AI of Set A, LSB of
for simplicity. To do Reversible Data hiding, a compressible
Subset of Set B, and the embedded secret data.
feature sequence should be first extracted from the original
cover. For this 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:
Figure
3.
Pixel
Dividation
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V. ADVANTAGES AND DISADVANTAGES
payload-distortion performance of the proposed scheme is
very good. For the smooth host images, the proposed
Advantages:
scheme significantly outperforms the previous reversible
A smart prediction method is exploited to make the
data hiding methods. The generated available cover values
estimation errors closer to zero, and better performance can
used the optimal transfer mechanism which is independent.
be achieved, but computation complexity will be higher due
In other words, new rule of value modification used the
to the prediction. The payload-distortion performance
optimal transfer mechanism and can be used on various
excellent of this proposed scheme. The host image is divided
cover values. If a smarter prediction method is shown to
into number of subsets and the auxiliary information of a
make the estimation errors closer to zero and a good
subset is embedded into the estimation errors in the next
performance can be achieved, but the computation
subset. By this way, one can successfully extract embedded
complexity will be higher due to the prediction. The
secret data and recover the original contents in the subsets
combination other kinds of available cover data and the
with an inverse order.
optimal transfer mechanism used further study in the future.
Disadvantages:
VII. FUTURE ENHANCEMENT
A spare place can always be made available In these
We like to propose future enhancement in our reversible
reversible data hiding methods to accommodate secret data
watermarking scheme. Local specifies of the image can be
as long as the chosen item is compressible, and the
managed by histogram shifting modulation technique. This
capacities are not very high. Payload of this method is low
can be apply to image prediction-errors and by using their
therefore each block can carry one bit.
neighborhood values, we can apply data in textured areas.
This is not achieved by other methods but histogram shifting
VI. CONCLUSION
In order carry through
modulation technique can do so.
a good payload-distortion
Also, we can select parts of the image which can be
performance of reversible data hiding,.This work find first
watermarked with the most suitable reversible modulation
the optimal value transfer matrix by maximizing a target
by using classification process.The reference image is used
function of pure payload with an repeating procedure, and
to generate classification, predication of it, having property
then proposes a practical reversible data hiding scheme. The
of being invariant to the watermark insertion. Using this
differences between the original pixel-values and the
method, the watermark embedded and extractor remain same
corresponding values calculate approximately from the
for message extraction as well as reconstruction.
neighbors .That are used to carry the payload that is made
VIII. REFERENCES
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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
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