visual cryptography based on image division using perfect square

Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
VISUAL CRYPTOGRAPHY BASED
ON IMAGE DIVISION USING
PERFECT SQUARE METHOD
Prameela1 , Geethalaxmi2
pramila.p63@g mail.co m1 , geethalaxmi@g mail.co m2
1
2
Dept. of CSE Canara Engineering College Mangalore,
Asst Prof. Dept of CSE/ISE Canara Eng ineering College Mangalore
Abstract: Visual cryptography an emerging
cryptography
technology
uses
the
characteristics of human vision to decrypt
encrypted images. It does not require the
knowledge of basic cryptography nor does it
need any complex computation. For security
concerns, it also ensures that hackers cannot
perceive any clues about a secret image from
individual cover images. In this visual
cryptography paper we propose to split the
image in to several square parts. These parts
are made such a way that each part is the split
of the image, selected so that individual part of
the split is a perfect square. Further in case of
higher security it is desired to have a simple
half tone method for the same square split
images. In case of image is already of the size
of perfect square, then this image is divided in
to a given n, where n is a perfect square of any
integer. This paper studies the characteristics
and application of perfect square split image
cryptographic method.
Key points: visual cryptography, perfect
square division method, Halftone.
I. INTRODUCTION
Security has become an inseparable issue as
information technology is ruling the world
now. Cryptography is the study of
mathematical techniques related aspects of
Information Security such as confidentiality,
22
Prameela, Geethalaxmi
data security, entity authentication and data
origin authentication, but it is not the only
means of providing information security,
rather one of the techniques. Visual
cryptography is a new technique which
provides information security which uses
simple algorithm unlike the complex,
computationally intensive algorithms used in
other techniques like traditional cryptography,
but it is applied only for image format. Visual
cryptography is a cryptographic technique
which allows visual information to be
encrypted in such a way that the decryption is
performed to obtain the original image [1][3].
In Visual Cryptography scheme, an image is
broken up into n shares, when all n shares are
stacking over together original image is
obtained, when less then n shares stacking
over together it can not reveal the original
image. Many works in this area have been
done and several algorithms have been
developed.
One of the popular techniques in a visual
cryptography is halftone methodology,
Halftone visual cryptography (HVC) is a kind
of visual secret sharing scheme [5], which can
decode a secret image by overlapping multiple
binary share images optically while the secret
image does not appear on each share image. A
halftone method is used to generate a binary
share image from a RGB [9]; meaning HVC
differs from watermark and other visual secret
Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
sharing (VSS) schemes. A watermark scheme
hides information into a single image, while
HVC hides the secret image into several share
images. HVC has wide applications, such as
the management of secret information,
copyright
protection,
authentication,
entertainment, and so on. The general
requirements for HVC are high quality of
share images, high processing speed,
invisibility of the secret image on share
images, and good visibility of decoded secret
images.
II. LITERATURE REVIEW
In 1994 Naor and Shamir [1] Proposed Visual
Cryptography Scheme (VCS) which is a
simple and secure method that allows sharing
of secret without
the need of any
cryptographic computations. To encode the
image, original image is split into n modified
versions referred as shares. Decoding can be
done by simply stacking subset S of those n
shares. G. Ateniese describes the following
four
different
methods
they
are
(2,2),(2,n),(n,n),(k,n). In (k,n) Basic model
any ‘k’ shares will decode the secret image
which reduces security level. To overcome
this issue the basic model is extended to
general access structures by G. Ateniese, C.
Blundo, A. De Santis, and D. R. Stinson [2],
where an access structure is a specification of
all qualified and forbidden subsets of ‘n’
shares. Any subset of ‘k’ or more qualified
shares can decrypt the secret image but no
information can be obtained by stacking lesser
number of qualified shares or by stacking
disqualified shares. Construction of k out of n
threshold visual cryptography scheme for
general access structure is better with respect
to pixel expansion Basic visual cryptography
is based on breaking of pixels into some subpixels or we can say expansion of pixels. Fig.1
below shows two approaches for (2,2)
threshold VCS.
23
Prameela, Geethalaxmi
Figure .1 Different methods of Visual
Cryptography
Visual cryptography were restricted to binary
images which is insufficient in real time
applications. Chang- ChouLin, Wen-Hsiang
Tsai [3] proposed visual cryptography for gray
level images by dithering techniques. Instead
of using gray sub pixels directly to constructed
shares, a dithering technique is used to convert
gray level images into approximate binary
images. The effect of this scheme is still
satisfactory in the aspects of increase in
relative size and decoded image quality, even
when the number of gray levels in the original
image still reaches 256. In traditional Color
Visual Cryptography, loss of contrast makes
VCS practical only when quality is not an
issue, which is quite rare. Previous methods
show good results for black and white or gray
scale VC schemes, however, they are not
sufficient to be applied directly to color shares
due
to
different
color
structures.
Dr.D.Vasumathi, M.Surya Prakash Rao,
M.Upendra
Kumar,
Dr.Y.Ramadevi
and,Dr.R.Rajeswara Rao[4] introduces the
concept of visual information pixel (VIP)
synchronization and error diffusion to attain a
color visual cryptography encryption method
that produces meaningful color shares with
high visual quality. VIP synchronization
retains the positions of pixels carrying visual
information of original images throughout the
color channels and error diffusion generates
shares pleasant to human eyes. A new method
of “Extended Visual Cryptography for natural
images” is used to produce a meaningful
Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
binary share which is predicted by Nakajima
[5]. Generally, visual cryptography suffers
from the deterioration of the image quality.
The meaningful shares generated in Extended
visual cryptography proposed by Mizuho
NAKAJIMA and Yasushi YAMAGUCHI [5]
was of poor quality which again increases the
suspicion of data encryption. Zhi Zhou,
Gonzalo R. Arce, and Giovanni Di Crescenzo
proposed halftone visual cryptography[6]
which increases the quality of the meaningful
shares. In halftone visual cryptography a
secret binary pixel ‘P’ is encoded into an array
of Q1 x Q2 (‘m’ in basic model) sub pixels,
referred to as halftone cell, in each of the ‘n’
shares. By using halftone cells with an
appropriate size, visually pleasing halftone
shares can be obtained. Also maintains
contrast and security. C. M. Hu and W. G.
Tzeng, Cheating Prevention in Visual
Cryptography [7] here we can study the
cheating problem in VC and extended VC.
Here they considered the attacks of malicious
adversaries who may deviate from the scheme
in any way. They proposed a generic method
that converts a VCS to another VCS that has
the property of cheating prevention. In the
basic visual cryptography numbers of shares
have been generated from one image. The
shares are sent through any channel to the
receiver and the receiver can again produce
original image by stacking all the shares in
proper order. This method wastes a lot of
bandwidth of the network. The techniques of
generating shares have been used in several
existing methods which are not unique. To
overcome this Satyendra Nath Mandal,
Subhankar Dutta and Ritam Sarkar[8]
proposed a block based symmetry key visual
cryptography algorithm to convert image in
encrypted form and decrypt the encrypted
image into original form. The symmetric key
has been generated from a real number. The
encryption and decryption algorithm have
been designed based on symmetry key. The
real number has been used to form the key
24
Prameela, Geethalaxmi
may be predefined or may be sent by secure
channel to the receiver. This algorithm can be
applied to any type of image that is binary,
gray scale and color images.
In this paper we proposed, to split the image
into n number of perfect square parts. These
parts are made such a way that each part is the
split of the image, selected so that individual
part of the split is a perfect square. In case of
image is already of the size of perfect square,
then this image is divided in to a given n,
where n is a perfect square of any integer. To
provide further more security here we using
halftone method.
III. PROPOSED SYSTEM
In this paper we are introducing splitting an
image into perfect squares. Splitting is done
by based on their height and width. These
parts are made such a way that each part is the
split of the original image, selected so that
individual part of the split is a perfect square.
Splitting the images it uses the recursive
algorithm procedure.
The objectives of this proposed system is:
•
To present perfect square method
scheme for hiding an image secretly
•
Further use of cipher system for the
same algorithm to strengthen the security
•
Use this for communicating secret
keys or encode authentication information
•
Using secret sharing to enable storage
of extra information in the shares, thereby
decreasing network load and increasing
efficiency.
•
To get the mathematical structure for
the perfect square method of image sharing
scheme
Methodology:
Perfect square generation:
Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
Perfect square division method is used
split the image into perfect square. Each
split image will be in the form of perfect
square. Splitting the image mainly based
on the image height and width. If the
image is in the form of square then we can
easily generate the perfect square. This
provides the n*n equal share division. If
the image is in the form of rectangle then
we have to consider the height and width
of the image to split the image as a perfect
square, if height has smaller value then
perfect square generated based on height.
This represents like h*h and remaining
portion is w- h. If width has smaller value
then perfect square generated based on
width. This represents like w × w and
remaining portion is h - w. The procedure
is repeating until in this way we get a least
perfect square of image. It is just a
procedure
of
recursive
algorithm, Recursive algorithm which
obtains the result for the current input by
applying simple operations to the returned
value for the smaller input. This method is
similar to Euclidian algorithm to find GCD
of two numbers. However it stops with
minimum perfect square, not with zero
divisors. Using Euclidian algorithm to find
GCD technique can be used to find
computational
complexity
of
the
processes.
shown in fig.2. Each image will be in the form
of perfect square. The split images contain
secret information of image; sometimes that
information may visible to user, to avoid this
here we applying Halftone methodology to
provide further more security for these split
images
Halftone Method:
In halftone VC a secret binary pixel is
encoded into an array of sub pixels [5],
referred to as a halftone cell, in each of the
shares this is for a Binary image. Halftone
method is nothing but a breaking the pixel into
white and black and creating the share for
each pixel then overlaying the each share to
get an original image. For color image we
have to fix the threshold value while breaking
the pixel [9][10]. Threshold value can be fixed
according to bit level, color pixel has three
byte, and these three bytes average value is
used to fix the threshold value in a halftone
method. First it takes average value of all three
colors then it fixes the threshold range for
each particular color, the fig.3 shows halftone
methodology. Here P is 24 bit pixel RGB
image; pi is value of each pixel in a particular
color of RGB, n is the total number of pixel in
an RGB image and i value start from 0 to n.
Figure.3 Halftone Method
Figure.2 Perfect Square generation
Average of all Red(R) pixels:
Once we get the perfect square image we are
not going to splitting that image again, we are
going to splitting remaining portion of the
image until it will get least perfect square it
25 Prameela, Geethalaxmi
Less than (<) R Red color
Greater than (>) R other color
Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
R=
pir: value of each pixel in red color
Average of all Green (G) pixels:
Less than (<) G Green color
Figure.4 image.jpeg (original image
(630*400))
Greater than (>) G other color
G=
pig : value of each pixel in green color
Average of all Blue (B) pixels :
Less than (<) B Blue color
Greater than (>) B other color
Figure.5 Split images of an original image
B=
pib: value of each pixel in blue color
III. RESULT
In this work it takes an image of jpeg
format to provide spilt results. The original
image is taken of 630 X 400 pixels. The
original image is split based on height and
width in each iteration, until we receive non
divisible smallest perfect square. It has been
illustrated in fig.4 and fig.5. Halftone process,
as per the methodology given, is implemented
to get further security this is shown in fig.6.
This method can be implemented for any type
of image with varying height and width. In
case of same width and height, this method
proposes to divide the image in to pre defined
number of perfect squares. Further in the same
work it has been decided to try for the
evaluation of this work.
26
Prameela, Geethalaxmi
Figure 6. Halftone Results
IV. CONCLUSION
The sequence of generating split of perfect
square is a novel method in this proposed
system. Image of any dimensions can be split
in to several perfect squares. In case of trace,
Internati onal Journal of Innovations & Advancement in Computer Science
IJ IACS
ISSN 2347 – 8616
Volume 3, Issue 3
May 2014
that square is split in to several pre defined
squares, such that these traces made hidden
.To reinforce this method, it is also tried with
an introduction of halftone method. This will
strengthen the method further. However
introducing this visual cryptography will
increase the volume of the total space
requirement.
REFERENCES
[1]M. Noar and A. Shamir, "Visual
cryptography," Advances in Cryptology EUROCRYPT'94, pp. 1-12, 1995
[2]G.Ateniese,C.Blundo,A.DeSantis,D.R.S
tinson, “Visualcryptography for general access
structures”
,Proc.ICALP96,Springer,Berlin,1996, pp.416428.
[3] Chang-Chou Lin , Wen-Hsiang Tsai,
“Visual cryptography for gray- level images by
dithering techniques”, Pattern Recognition
Letters, v.24 n.1-3.
[4] Dr. S. Vasumathi, M. Surya Prakash Rao,
M. Upendra Kumar, „‟Novel Approach for
color Extended Visual Cryptography Using
Error Diffusion” International Journal of
Computer Trends and Technology- volume 3
Issue 4- 2012
[5] Z. Zhou, G.R. Arce and G. Crescenzo,
"Halftone visual cryptography," IEEE
27
Prameela, Geethalaxmi
Transactions on Image Processing, Vol. 15,
No. 8, pp. 2441-2453, 2006.
[6] Mizuho
Nakajima and
Yasushi
Yamaguchi, “Extended Visual Cryptography
for Natural Images”.
[7] C. M. Hu and W. G. Tzeng, “Cheating
Prevention in Visual Cryptography”,. IEEE
Transaction on Image Processing, vol. 16, no.
1, Jan-2007, pp. 36-45.
[8] Satyendra Nath Mandal, Subhankar Dutta
and Ritam Sarkar, “Block Based Symmetry
Key Visual Cryptography ”I. J. Computer
Network and Information Security, 2012, 9,
10-19
[9] Young-Chang Hou, "Visual cryptography
for color images," Pattern Recognition, Vol.
36, No. 7, pp. 1619-1629, 2003.
[10] Anil Kamboj, Kavita Grewal, Ruchi
Mittal “Color Edge Detection in RGB Color
Space Using Automatic Threshold Detection”
International
Journal
of
Innovative
Technology and Exploring Engineering
(IJITEE) ISSN: 2278-3075, Volume-1, Issue3, August 2012

Download Report