14-07-2014, 02:22 PM
An Adaptive Steganographic Technique Based On Integer Wavelet Transform
[attachment=65825]
Abstract
The need for providing secrecy in an open
environment made steganography important in the past years.
With almost anyone can observe the communicated data all
around, steganography attempts to hide the very existence of the
message and make communication undetectable. Many
techniques are used to secure information such as cryptography
that aims to scramble the information sent and make it
unreadable while steganography is used to conceal the
information so that no one can sense its existence. In most
algorithms used to secure information both steganography and
cryptography are used together to secure a part of information.
To hide the data in digital images by combining the use of
adapti ve hiding capacity function that hides secret data in the
integer wavelet coefficients of the cover image with the optimum
pixel adjustment (OPA) algorithm. The proposed system showed
high hiding rates with reasonable imperceptibility compared to
other steganographic systems
INTRODUCTION
Steganography is the art and science of hiding secret
data in plain sight without being noticed within an innocent
cover data so that it can be securely transmitted over a
network. The word steganography is originally composed of
two Greek words steganos and graphia, which means
"covered writing". The use of steganography dates back to
ancient times where it was used by romans and ancient
Egyptians. The interest in modem digital Steganography
started by Simmons in 1983 when he presented the problem
of two prisoners wishing to escape and being watched by the
warden that blocks any suspicious data communicated
between them and passes only normal looking one. Any
digital file such as image, video, audio, text or IP packets can
be used to hide secret message. Cover object, and the term
stego-object is used for the file containing secret message.
Among all digital file formats available nowadays
image files are the most popular cover objects because they
are easy to find and have higher degree of distortion tolerance
INTEGER WAVELET TRANSFORM
Generally wavelet domain allows us to hide data in
regions that the human visual system (HVS) is less sensitive
to, such as the high resolution detail bands (HL, LH and HH),
Hiding data in these regions allow us to increase the
robustness while maintaining good visual quality. Integer
wavelet transform maps an integer data set into another
integer data set. In discrete wavelet transform, the used
wavelet filters have floating point coefficients so that when
we hide data in their coefficients any truncations of the
floating point values of the pixels that should be integers may
cause the loss of the hidden information which may lead to the
failure of the data hiding system
PROPOSED SYSTEM
The proposed system is an adaptive data hiding
scheme, in which randomly selected integer wavelet
coefficients of the cover image are modified with secret
message bits. Each of these selected coefficients hide different
number of message bits according to the hiding capacity
function. After data insertion we apply optimum pixel
adjustment algorithm to reduce the error induced due to data
insertion. The block diagram is shown in "Fig. 2". We can say
that the proposed system is classified into three cases of
operation according to different applications; Low hiding
capacity with good visual quality (high value of peak signal to
noise ratio "PSNR"), average hiding capacity with reasonable
visual quality and high hiding capacity with low v
EXPERIMENTAL RESULTS
The proposed system was applied to two typical
512x512 8-bit grayscale images shown in figure 2, "chithra" ;
it achieved satisfactory results against other systems using
wavelet transform.
The program was implemented using Matlab 7.5
running on 2.93 G dual core processor under Windows Vista.
The secret message to embed is a randomly generated binary
stream with the same length as the calculated hiding capacity
CONCLUSIONS
In this paper we proposed a novel data hiding scheme
that hides data into the integer wavelet coefficients of an
image. The system combines an adaptive data hiding
technique and the optimum pixel adjustment algorithm to
increase the hiding capacity of the system compared to other
systems. The proposed system embeds secret data in a random
order using a secret key only known to both sender and
receiver. It is an adaptive system which embeds different
number of bits in each wavelet coefficicient according to a
hiding capacity function in order to maximize the hiding
capacity without sacrificing the visual quality of resulting
stego image. The proposed system also minimizes the
difference between original coefficients values and modified
values by using the optimum pixel adjustment algorithm. The
proposed scheme was classified into three cases of hiding
capacity according to different applications required by the
user. Each case has different visual quality of the stego-image.
Any data type can be used as the secret message since our
experiments was made on a binary stream of data. There was
no error in the recovered message (perfect recovery) at any
hiding rate. From the experiments and the obtained results the
proposed system proved to achieve high hiding capacity up to
48% of the cover image size with reasonable image quality
and high security because of using random insertion of the
secret message. On the other hand the system suffers from low
[attachment=65825]
Abstract
The need for providing secrecy in an open
environment made steganography important in the past years.
With almost anyone can observe the communicated data all
around, steganography attempts to hide the very existence of the
message and make communication undetectable. Many
techniques are used to secure information such as cryptography
that aims to scramble the information sent and make it
unreadable while steganography is used to conceal the
information so that no one can sense its existence. In most
algorithms used to secure information both steganography and
cryptography are used together to secure a part of information.
To hide the data in digital images by combining the use of
adapti ve hiding capacity function that hides secret data in the
integer wavelet coefficients of the cover image with the optimum
pixel adjustment (OPA) algorithm. The proposed system showed
high hiding rates with reasonable imperceptibility compared to
other steganographic systems
INTRODUCTION
Steganography is the art and science of hiding secret
data in plain sight without being noticed within an innocent
cover data so that it can be securely transmitted over a
network. The word steganography is originally composed of
two Greek words steganos and graphia, which means
"covered writing". The use of steganography dates back to
ancient times where it was used by romans and ancient
Egyptians. The interest in modem digital Steganography
started by Simmons in 1983 when he presented the problem
of two prisoners wishing to escape and being watched by the
warden that blocks any suspicious data communicated
between them and passes only normal looking one. Any
digital file such as image, video, audio, text or IP packets can
be used to hide secret message. Cover object, and the term
stego-object is used for the file containing secret message.
Among all digital file formats available nowadays
image files are the most popular cover objects because they
are easy to find and have higher degree of distortion tolerance
INTEGER WAVELET TRANSFORM
Generally wavelet domain allows us to hide data in
regions that the human visual system (HVS) is less sensitive
to, such as the high resolution detail bands (HL, LH and HH),
Hiding data in these regions allow us to increase the
robustness while maintaining good visual quality. Integer
wavelet transform maps an integer data set into another
integer data set. In discrete wavelet transform, the used
wavelet filters have floating point coefficients so that when
we hide data in their coefficients any truncations of the
floating point values of the pixels that should be integers may
cause the loss of the hidden information which may lead to the
failure of the data hiding system
PROPOSED SYSTEM
The proposed system is an adaptive data hiding
scheme, in which randomly selected integer wavelet
coefficients of the cover image are modified with secret
message bits. Each of these selected coefficients hide different
number of message bits according to the hiding capacity
function. After data insertion we apply optimum pixel
adjustment algorithm to reduce the error induced due to data
insertion. The block diagram is shown in "Fig. 2". We can say
that the proposed system is classified into three cases of
operation according to different applications; Low hiding
capacity with good visual quality (high value of peak signal to
noise ratio "PSNR"), average hiding capacity with reasonable
visual quality and high hiding capacity with low v
EXPERIMENTAL RESULTS
The proposed system was applied to two typical
512x512 8-bit grayscale images shown in figure 2, "chithra" ;
it achieved satisfactory results against other systems using
wavelet transform.
The program was implemented using Matlab 7.5
running on 2.93 G dual core processor under Windows Vista.
The secret message to embed is a randomly generated binary
stream with the same length as the calculated hiding capacity
CONCLUSIONS
In this paper we proposed a novel data hiding scheme
that hides data into the integer wavelet coefficients of an
image. The system combines an adaptive data hiding
technique and the optimum pixel adjustment algorithm to
increase the hiding capacity of the system compared to other
systems. The proposed system embeds secret data in a random
order using a secret key only known to both sender and
receiver. It is an adaptive system which embeds different
number of bits in each wavelet coefficicient according to a
hiding capacity function in order to maximize the hiding
capacity without sacrificing the visual quality of resulting
stego image. The proposed system also minimizes the
difference between original coefficients values and modified
values by using the optimum pixel adjustment algorithm. The
proposed scheme was classified into three cases of hiding
capacity according to different applications required by the
user. Each case has different visual quality of the stego-image.
Any data type can be used as the secret message since our
experiments was made on a binary stream of data. There was
no error in the recovered message (perfect recovery) at any
hiding rate. From the experiments and the obtained results the
proposed system proved to achieve high hiding capacity up to
48% of the cover image size with reasonable image quality
and high security because of using random insertion of the
secret message. On the other hand the system suffers from low