VISUAL CRYPTOGRAPHY BASED
ON IMAGE DIVISION USING
PERFECT SQUARE METHOD
Prameela1, Mrs. Geethalaxmi2
pramila.p63@gmail.com1, geethalaxmi@gmail.com2
1
Dept. of CSE Canara Engineering College Mangalore,
2
Asst Prof. Dept of CSE/ISE Canara Engineering 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, 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 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 sub-pixels
or we can say expansion of pixels. Fig.1 below
shows two approaches for (2,2) threshold VCS.
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 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 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:
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.
Figure.3 Halftone Method
Average of all Red(R) pixels:
Figure.2 Perfect Square generation
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 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
Less than (<) R Red color
Greater than (>) R other color
R = 1/𝑛 ∑𝑛𝑖=1 p𝑖𝑟
pir: value of each pixel in red color
Average of all Green (G) pixels:
Less than (<) G Green color
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.
Greater than (>) G other color
G = 1/𝑛 ∑𝑛𝑖=1 p𝑖𝑔
pig: value of each pixel in green color
Average of all Blue (B) pixels :
Less than (<) B Blue color
Greater than (>) B other color
B = 1/𝑛 ∑𝑛𝑖=1 p𝑖𝑏
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.
to several perfect squares. In case of trace, 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
Figure.4 image.jpeg (original image (630*400))
[2]G.Ateniese,C.Blundo,A.DeSantis,D.R.S
tinson, “Visualcryptography for general access
structures” ,Proc.ICALP96,Springer,Berlin,1996,
pp.416-428.
[3] Chang-Chou Lin , Wen-Hsiang Tsai, “Visual
cryptography for gray-level images by dithering
techniques”, Pattern Recognition Letters, v.24
n.1-3.
Figure.5 Split images of an original image
[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
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.
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
[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: 22783075, Volume-1, Issue-3, August 2012