  With rapid advances in digital information processing systems, and more
specifically in digital image processing software, there is a widespread
development of advanced tools and techniques for digital image forgery. One of
the techniques most commonly used is the Copy-move forgery which proceeds by
copying a part of an image and pasting it into the same image, in order to
maliciously hide an object or a region. In this paper, we propose a method to
detect this specific kind of counterfeit. Firstly, the color image is converted
from RGB color space to YCbCr color space and then the R, G, B and Y-component
are splitted into fixed-size overlapping blocks and, features are extracted
from the R, G and B-components image blocks on one hand and on the other, from
the DCT representation of the R, G, B and Ycomponent image block. The feature
vectors obtained are then lexicographically sorted to make similar image blocks
neighbors and duplicated image blocks are identified using Euclidean distance
as similarity criterion. Experimental results showed that the proposed method
can detect the duplicated regions when there is more than one copy move forged
area in the image and even in case of slight rotations, JPEG compression,
shift, scale, blur and noise addition.
