Abstract:
Copy-Move forgery is a type of image forgery
wherein a patch from the image is copied and pasted on the same
image either to increase the occurrence of a particular object
or to conceal some important detail in the image. This paper
addresses the issue of copy-move forgery using the block-based
method of feature extraction. In block-based methods of feature
extraction, PHT is one of the competing solutions, but it is not
much robust to scaling. This paper proposes Scale-Invariant Fast
PHT (SIFPHT) algorithm to detect the copy-move forgery which
uses Fast PHT [1] for extracting the features from the blocks.
Fast PHT has a higher convergence rate than the traditional PHT,
and the results prove that the speed-up of almost 4 is attained
for detecting the forgery. Moreover, the Fast PHT features so
obtained from the blocks are normalized before comparison due
to which the scaled forged segments are also identified. Further,
Fast K-Means clustering is used to estimate the similarity in the
blocks and hence detect the copy-move forgery.
