19-03-2014, 10:24 AM
Comparison analysis of spatial Domain and compressed Domain steganographic techniques
Comparison analysis .pdf (Size: 521.87 KB / Downloads: 22)
Abstract:
Steganography plays an important role in the past
few years due to the increasing need for providing
secrecy in an open environment like the internet.
Many techniques are used to secure information
such as Cryptography that aims to scramble the
information sent and makes it unreadable while
steganography is used to conceal the information so
that no one can sense its existence. Steganography has
many technical challenges such as high hiding
capacity and imperceptibility. In this paper we
compared two proposed techniques, one with
wavelet transforms and other with block truncation
coding. First method hides secret data in the integer
wavelet coefficients of the cover image with the
optimum pixel adjustment (OPA) algorithm. The
coefficients used are selected according to a
pseudorandom function generator to increase the
security of the hidden data.
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 Grahiia, which means ―covered
writing ―.The use of Steganography dates back to
ancient times where it was used by roman’s and
ancient Egyptians. The interest in modern digital
steganography stated by Simmonsin 1983[1]
Steganography using spatial domain:
In this technology embedding is done by using
Integer Wavelet Coefficients. Generally wavelet
domain allows to hide data in regions that the
Human Visual System (HVS) is less sensitive to the
hiding resolution detail band (HL, LH, HH). Hiding
data in these regions allows us to increase the
robustness while maintaining good visual quality.
Integer wavelet transform maps an integer data set
into another integer data set. LL sub band in IWT
appears to be a close copy with smaller scale of
original image[5].
Conclusions:
In this paper, we compared two proposed
steganographic techniques; one is based on spatial
domain (by Integer Wavelet Transforms) other one
is based on compressed domain (Block Truncation
Coding). It is well known that, although the data
hiding techniques can recover the original image
after the extraction of secret data, the embedding
distortion needs to be kept as low as possible in
order to achieve perceptually invisible. In our
schemes, the process of data embedding does not
introduce any image distortion, which should be the
best case for steganography.