Dft based individual extraction of steganographic compression of images

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 02 | Feb-2014, Available @ http://www.ijret.org 199
DFT BASED INDIVIDUAL EXTRACTION OF STEGANOGRAPHIC
COMPRESSION OF IMAGES
C. Rengarajaswamy1
1
Assistant Professor, Department of Electronics and Communication Engineering, M.A.M School of Engineering, Trichy,
Tamil Nadu
Abstract
A Novel scheme of Separable Extraction of concealed data and compressed image is proposed adopting a transform based
compression over the encrypted data. Reversible data hiding is branched under Steganography. In this reversible data hiding the art
of concealing a secret data over the cover image is practiced. More than that, the main ingredients that play the key role are
encryption key and the data hiding key, the compression is performed in between the two processes i.e., encryption and data hiding, to
create a spare space to accommodate the secret data. The main aim of this proposed scheme is to limit the distortion and to enhance a
wide space for concealing of the secret data i.e., to increase the embedding rate. The compression here classified into lossy and
lossless. Lossy compression best suits for image and audio (telephone conversation, etc.) whereas lossless compression needed in the
text and videos. Hence to perform the lossless compression over a stegomized image and improve its secrecy, DFT is performed after
Encryption.
Keywords: DFT, Data Embedding, RDH, Separable RDH, Compression
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1. INTRODUCTION
In the world of communication, security plays a vital role and
owns a major regime on its stack. The word communication
now a day’s does not travel alone, but hand in hand with
security aspects. Thus security turns to be the key to unlock a
communication box. Coming to security, which is branched
into cryptography, information hiding and watermarking etc,
provides better role as they take part. As the technology keeps
on changing its face with advanced features, there is need to
get updated to it in its long run towards the betterment of
future. Usually the happening is that when a new algorithm is
produced or an existing algorithm is revised, intruders or
hackers break the algorithm. So it is a must to develop
algorithms more efficient and be stable and unbreakable to
most extent. Normally, the network security is branched into
cryptography and information hiding. Information hiding
contains Steganography and watermarking which may be
dated back old compared to cryptography. In cryptography,
scramble of data’s takes place at the transmitter and
unscrambling them gives the exact input at the receiver
section. Thus for scrambling and unscrambling denoted
technically as encryption and decryption, a key is used. Thus
to encrypt and decrypt same key or different keys may be
used. Further extending its branches into symmetric
(conventional) and asymmetric (public key) encryption. Here
in the former encryption, same key is used both at the
transmitter and receiver. Bit in the later case, different key is
handled. Coming to Steganography, which is art of concealing
of data into other. It may be dated past, but again heads to
more secure transmission. In order to improve the security
level, combination of various techniques is handled. One such
try is the Steganography over cryptography. Thus both the
techniques provide better authentication and integrity among
the users. One such technique chosen under Steganography is
RDH (Reversible Data Hiding). In RDH, major ingredients are
the cover data and the secret data. Cover data is which the
secret data to be hidden, like the letter enclosed in an
envelope. The other is secret or additional data. Here the
overall data enclosing the cover data and secret data is called
the marked cover. In RDH more importance is given to the
cover data, such that the user information is inscribed over it.
There is a lot application employing RDH mainly in the case
of military communication, patient details, in case of
emergency over country, etc. The below diagram illustrates
the basic block of how RDH is processed through. Thus
embedding secret data to the cover data at transmitter and the
reverse process explains abut extracting the secret data as well
as the cover data without any error, if error data not recovered.
The later part of this paper is lapsed as follows. Section II
comprises related works describing RDH and its separable
extension. Section III describes the proposed work handling
stream cipher encryption and DFT compression and
embedding. Section IV gives us the exact view of the
proposed scheme as the experimental results using Image
Processing Tool. Section V summarizes the whole content to a
short and sweet manner. Further, in section VI the references
are listed.

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Fig 1 Basic Block diagram of RDH
2. RELATED WORKS
2.1 Embedding in LSB
A digital image is basically divided into pixels. These pixel
values may vary for each type of images. For a Binary image,
the pixel value is 1, for gray scale and color the range of pixel
is 8-bit and 24-bit. So to carry the LSB embedding process,
mostly gray scale and color images are preferred. Here in LSB
only the least bits of a pixel is altered or cleared to embed the
secret or additional data. If any change is made in the MSB
bits, they change the whole nature of the Image. Here the
Payload Data (secret Data) is embedded in such a way that can
be reconstructed only at the receiving end. The common
procedure that is carried out to embed a payload data is given
by the formula [1],
Si = Ci + Ci mod 2k
+ mi
Here Si - stego image, Ci - the cover image, k - the embedding
parameter and mi - the payload.
Thus LSB is the most basic method and used in common for
creating the sparse space. Thus the sparse space created is
useful for hiding the additional payload data. This makes the
work easier. Hence at the extraction part it is easier to retrieve
the original message as well as the secret data with low data
loss.
2.2 Reversible Data Hiding
Reversible data hiding (RDH) is a technique which is entirely
different from other substitution techniques. In RDH, the main
aim is to recover the data without any error. If there is any
error either in the cover data or the secret explained as
follows. The above diagram shows us how the process is
successfully carried out using RDH. The RDH consists of two
steps each carried at the transmitter and the receiver end. At
the transmitter side the data is embedded into the cover image
in the sparse space already created to hide data. Here the
additional data hidden in done using the data-hiding key, so
that the same key is used at the receiver to recover the secret
data. As soon as the compression and embedding process the
data is passed to the receiving end along with the data-hiding
key. In the receiver end, the extraction process is carried out
using the same data-hiding key.
During this process if any change is done in the transmitted
data, it causes some error in the transmitted data. Thus if any
error occurs either in the cover image r the secret data, the
original data cannot be retrieved. This is the special property
of using RDH which provides additional authentication and
integrity.
2.3 RDH over Encrypted Images
In this section, RDH is performed over an encrypted Image.
Thus it carries three steps and two keys which is same for both
the transmitter and the receiver. The first is encryption using
encryption key and sparse space creation and third is the data
embedding using data-hiding key. The receiver is done in an
orderly process i.e., decryption using the encryption key to
recover the cover image and then applying the data-hiding key
to recover the secret data. If any key is applied without the
specified manner the cover image and the secret data cannot
be recovered, which is a unique property of RDH [2].
2.4 Separable RDH over Encrypted Images
In the earlier method proposed [2], at the receiver end
decryption is performed first in order to extract the cover
image and then applying the data-hiding key to recover the
secret data, which is non-separable in manner. In the case of
separable RDH, either of the key can be used irrespective of
the other to recover the respective data’s independently [3]
Insecure
Channel
Cover
Image
Secret
Image
Embedding
process
Marked
Cover
Transmitter
Marked
Cover
Extraction
process
Cover
Image
Secret
Image
Receiver

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was proposed. This proves to be better flexible among the user
handling different keys.
Fig 2 Proposed RDH using DFT
3. PROPOSED SCHEME
3.1 Encryption Using Stream Cipher
In the encryption part, it is a must to choose what type of
encryption is adopted and which is best suitable. Stream
cipher encryption is chosen despite its high security and
flexibility. In stream cipher, the encryption in carried as bit by
bit format, whereas in the block cipher, an entire block is
subjected to encryption. In stream cipher, a raw data is XOR-
ed with the randomly generated key by the pseudorandom
generator. The pseudo random generated key is used both at
the transmitter and the receiver. Thus the same key is used to
decrypt the data at the receiver end, hence the name symmetric
key encryption.
Di,j,u = di,j,u ki,j,u
Here i,j represents the row and column of the image and u
represents the face value of each bit in the pixel. In this
encryption, each bit of the pixel is XOR-ed with the key
generated by the pseudorandom generator. As the encryption
key is pseudo randomly generated and reproduced only at the
receiving end, which cannot be produced by any intruders and
is difficult to break or analyze the image. A basic algorithm
for stream cipher is RC4 provides better security. Thus each
and every bit in the data is encrypted and is highly secured.
3.2 Compression using DFT and Data Embedding
Compression is a technique for reducing the file size making it
suitable for data transmission. There are two types of
compression, namely lossless and lossy. Image in its 2-D form
can be compressed using various techniques. One primary
method is to use Discrete Fourier transform (DFT). DFT gives
the better approximation of Fourier transform on discrete set
of frequencies. The spatial values in such 2-dimension is
represented as f(x,y). The transformed image is represented as
F(u,v).
𝐹 𝑢, 𝑣 =
1
𝑀. 𝑁
𝑓(𝑥, 𝑦)𝑒−𝑗2𝜋 (
𝑢𝑥
𝑀
+
𝑣𝑦
𝑁
)
𝑁−1
𝑦=0
𝑀−1
𝑥=0
The inverse Fourier transform is thus given by,
𝑓 𝑥, 𝑦 =
1
𝑀. 𝑁
𝐹(𝑢, 𝑣)𝑒 𝑗2𝜋 (
𝑢𝑥
𝑀
+
𝑣𝑦
𝑁
)
𝑁−1
𝑣=0
𝑀−1
𝑢=0
Stream Cipher
Encryption
DFT
Compression
Information
Hiding
Encryption
Key
Cover Image
Secret
Image
Stego Image
Compressed Image
Data Extraction
DFT
Decompression
Decryption
Original Cover Image
Encryption
Key

__________________________________________________________________________________________
Fig 3 Separable Receiver Section
The transform equation suggests that an image of size MxN
with spatial values (x,y) is transformed into one with values
(u,v) [4].
Fast Fourier Transform (FFT) is the fastest method of DFT.
FFT is a high speed and efficient technique. At the
reconstruction stage, the image compressed using lossless
method will have better image quality than the one that is
compressed using lossy method [5].
3.3 Decryption and Extraction
In the receiver side, the reverse process is carried out [3]. Here
as the data is received they can be separately extracted
independently using either the encryption key which is pseudo
randomly generated to extract the decrypted image. Here the
same pseudo random generated must be provided by the
receiver in order to extract the cover image. Then the data-
hiding key is applied to the recovered image to extract the
secret data. The keys can be used alternatively to recover any
one of the data also. Hence offer better flexibility.
4. EXPERIMENTAL RESULTS
(a) Original Cover Image
(b) Stream Ciphered Image
(c) Secret Image
Case 1
Data Extraction
Encrypted image
containing
embedded data
Data Hiding Key
Additional Data
Case 2
Image Decryption
Encrypted image
containing
embedded data
Encryption Key
Decrypted Image

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(d) Stego Image Containing Secret Image
(e) Extracted Secret Image
Fig. 4 Implemented Outputs
The figure above shows the results of the proposed system.
Initially, an image taken is considered to be a cover image.
This image is now given for DFT compression after which the
secret image is embedded into the cover. The obtained stego
image is then given into a separable receiver for separable
extraction of original image and the secret image.
CONCLUSIONS
In this paper we briefly discuss about how to encrypt a data,
compress the encrypted data and embed a data to the
compressed one. The later part explains about the extraction
and decryption. To summarize all this, at the transmitter side
an encryption is carried using the encryption. Then the DFT
compression is done to the encrypted image to create the space
needed to hide the secret image. In the free space provided the
additional secret data is embedded using the data-hiding key.
DFT thus provides efficient compression in the frequency
domain basis. Then at the receiver side, either of the key is
used independently to recover the cover image and the secret
data separately. Among more other compression techniques
DFT operates well in the frequency domain which is best
suited for audio and images. Hereby concluding that DFT
provided best compression rate and loss is a least part
considering.
REFERENCES
[1]. C. K. Chan and L. M. Cheng, “Hiding data in images by
simple LSB substitution,” Pattern Recognit., vol. 37, no. 3, pp.
469–474, 2004.
[2]. Manikandan R Asst. Professor, Uma M ,
MahalakshmiPreethi S M, “Reversible Data Hiding for
Encrypted Image”, Journal of Computer Applications ISSN:
0974 – 1925,Volume-5, Issue EICA2012-1, February 10, 2012
[3]. X. Zhang, “Reversible data hiding in encrypted image,”
IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255–258, Apr.
2011.
[4]. Inderjit Singh, Sunil Khullar, Dr. S.C. Laroiya, “DFT
Based Image Enhancement and Steganography”, International
Journal of Computer Science and Communication
Engineering, ISSN : 2319-7080, Vol2, Issue 1, Feb 2013.
[5]. Mridul Kumar Mathur, Gunjan Mathur, “ Image
Compression using DFT through Fast Fourier Transform
Technique”, International Journal of Emerging Trends and
Technology in Computer Science”, ISSN : 2278-6856, Vol 1,
Issue 2, July-Aug 2012.

Dft based individual extraction of steganographic compression of images

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