17-06-2014, 11:54 AM
Detecting Copy-Move Forgery in Digital Images: A Survey and Analysis of Current Methods
Detecting Copy-Move Forgery.pdf (Size: 512.8 KB / Downloads: 28)
Abstract
As one of the most successful applications of image
analysis and understanding, digital image forgery detection has
recently received significant attention, especially during the
past few years. At least two trend account for this: the first
accepting digital image as official document has become a
common practice, and the second the availability of low cost
technology in which the image could be easily manipulated.
Even though there are many systems to detect the digital image
forgery, their success is limited by the conditions imposed by
many applications. For example, detecting duplicated region
that have been rotated in different angles remains largely
unsolved problem. In an attempt to assist these efforts, this
paper surveys the recent development in the field of Copy-
Move digital image forgery detection.
Keyword-Image forgeries, Digital forensics, Copy-Move
forgery detection, block matching
NTRODUCTION
rom the early days an image has generally been accepted
as a proof of occurrence of the depicted event.
Computer becoming more prevalent in business and other
field, accepting digital image as official document has
become a common practice. The availability of low-cost
hardware and software tools, makes it easy to create, alter,
and manipulated digital images with no obvious traces of
having been subjected to any of these operations. As result
we are rapidly reaching a situation where one can no longer
take the integrity and authenticity of digital images for
granted. This trend undermines the credibility of digital
images presented as evidence in a court of law, as news
items, as part of a medical records or as financial documents
since it may no longer be possible to distinguish whether a
given digital images is original or a modified version or
even a depiction of a real-life occurrences and objects.
Digital image forgery is a growing problem in criminal
cases and in public course. Currently there are no
established methodologies to verify the authenticity and
integrity of digital images in an automatic manner.
Detecting forgery in digital images is an emerging research
field with important implications for ensuring the credibility
of digital images [1]. In the recent past large amount of
digital image manipulation could be seen in tabloid
magazine, fashion Industry, Scientific Journals, Court
rooms, main media outlet and photo hoaxes we receive in
COPY-MOVE FORGERY DETECTION TECHNIQUES
The simplest way to detect a Copy-Move forgery is to use
an exhaustive search. In this approach, the image and its
circularly shifted version are overlaid looking for closely
matching image block. This approach is simple and effective
for small-sized images. However, this method is
computational expensive and even impractical for image of
medium-sized. In this method for an image size it
would take 2 steps, since the comparison and image
processing require the order of operations for one shift..
Another technique for detecting forgery is based on
autocorrelation. All Copy-Move forgery introduces a
correlation between the original segment and the pasted one.
However, this method does not have large computational
complexity and often fail to detect forgery.
However, in most other approaches the detected image is
divided into overlapping blocks. The idea here is to detect
connected blocks that are copied and moved. The copied
region would consist many overlapping blocks. The distance
between each duplicated block pair would be same since
each block are moved with same amount of shift. The next
challenge would be extracting features form these blocks,
which would yield to very similar or same values for
duplicated block. Several authors presented to use different
features to represent the image block. These blocks are
vectorized and inserted into a matrix and the vectors are
lexicographically sorted for later detection. The
computational time depends upon factor such as number of
blocks, sorting techniques and the number of feature.
Suppose an image size is , it is
CONCLUSION
As Copy-Move forgeries have become popular, the
importance of forgery detection is much increased.
Although many Copy-Move Forgery detection techniques
have been proposed and have shown significant promise,
robust forgery detection is still difficult. There are at least
three major challenges: tampered images with compression,
tampered images with noise, and tampered images with
rotation. In this paper we reviewed several papers to know
the recent development in the field of Copy-Move digital
image forgery detection. Sophisticated tools and advanced
manipulation techniques have made forgery detection a
challenging one. Digital image forensic is still a growing
area and lot of research needed to be done.