01-06-2012, 03:54 PM
AN IMPROVED VISUAL CRYPTOGRAPHY SCHEME FOR SECRET HIDING
AN IMPROVED VISUAL CRYPTOGRAPHY SCHEME FOR SECRET HIDING.pdf (Size: 304.11 KB / Downloads: 86)
INTRODUCTION
Visual cryptography, introduced by Naor and
Shamir in 1995 [2], is a new cryptographic scheme where
the ciphertext is decoded by the human visual system.
Hence, there is no need to any complex cryptographic
computation for decryption. The idea is to hide a secret
message (text, handwriting, picture, etc…) in different
images called shares or cover images. When the shares
(transparencies) are stacked together in order to align the
subpixels, the secret message can be recovered. The
simplest case is the 2 out of 2 scheme where the secret
message is hidden in 2 shares, both needed for a successful
decryption [2]. This can be further extended to the k out of
n scheme where a secret message is encrypted into n shares
but only k shares are needed for decryption where k≤ n. If
k-1 shares are presented, this will give no information
about the secret message.
DEVELOPMENT
Chang’s et al. Algorithm
Chang et al. proposed in 2002 a new secret
color image sharing scheme [1] based on modified visual
cryptography. The proposed approach uses meaningful
shares (cover images) to hide the colored secret image and
the recovery process is lossless. The scheme defines a new
stacking operation (XOR) and requires a sequence of
random bits to be generated for each pixel. Chang’s
scheme can be generalized to an n out of n approach as
opposed to Chang Tsai’s scheme presented previously.
Recovering Algorithm
In order to recover the secret image in a 2 out of 2 scheme,
both camouflage images O1’, O2’ as well as the string of
random bits R are required for the recovery process (Fig.
2). The camouflage images are t time bigger than IHL due to
the expansion factor of subpixels.
Improved image generation scheme
In this section, we introduce a modification of Chang's
algorithm to generate better quality camouflage images.
Most of the modifications are applied to the subpixel
expansion block described in the next section.
Hiding Algorithm
Before subpixel expansion, add one to all pixels in the
cover images and limit their maximum value to 255. This
ensures that no “0” valued pixels exist in the images. When
the images are expanded, replace all the 0’s in S0, S1 by
values corresponding to k1-1 in B1 and k2-1 in B2 (Figure 3)
instead of leaving them transparent. Also, adjust all pixel
values to be between 0-255
RESULTS
A 100x100 secret image (forest) is hidden
into two 100x100 cover images (snow and jet). As seen in
Figure 4 (d, e), the camouflage images obtained using the
original algorithm are noisy and of poor resolution.
However, the recovery process is lossless and the used
cover images are meaningful. Figure 5 (a, b) shows the
camouflage obtained using the enhanced algorithm where
noise is considerably reduced while achieving lossless
recovery of the secret message.
DISCUSSION AND CONLUSION
This paper presented a new technique based on
Chang et al. algorithm [5] to hide a color secret image into
multiple colored images. The generated camouflage images
contain less noise compared to the ones previously
obtained (Fig. 4, 5) using the original Chang’s embedding
algorithm. This results in a considerable improvement in
the signal to noise ratio of the camouflage images by
producing images with similar quality to the originals. An
improvement in signal to noise ration of 9.3 dB and 19.97
dB were obtained for the initial camouflage images used
for hiding the secret image. This developed method does
not require any additional cryptographic computations and
achieves a lossless recovery of the secret image. In
addition, the camouflage images obtained using the
modified algorithm look less susceptible of containing a
secret message than the ones obtained using the original
method.