  Copy-move forgery is the most popular and simplest image manipulation method.
In this type of forgery, an area from the image copied, then after post
processing such as rotation and scaling, placed on the destination. The goal of
Copy-move forgery is to hide or duplicate one or more objects in the image.
Key-point based Copy-move forgery detection methods have five main steps:
preprocessing, feature extraction, matching, transform estimation and post
processing that matching and transform estimation have important effect on the
detection. More over the error could happens in some steps due to the noise.
The existing methods process these steps separately and in case of having an
error in a step, this error could be propagated to the following steps and
affects the detection. To solve the above mentioned problem, in this paper the
steps of the detection system interact with each other and if an error happens
in a step, following steps are trying to detect and solve it. We formulate this
interaction by defining and optimizing a cost function. This function includes
matching and transform estimation steps. Then in an iterative procedure the
steps are executed and in case of detecting error, the error will be corrected.
The efficiency of the proposed method analyzed in diverse cases such as pixel
image precision level on the simple forgery images, robustness to the rotation
and scaling, detecting professional forgery images and the precision of the
transformation matrix. The results indicate the better efficiency of the
proposed method.
