Statistical Approach for Copy Move Forgery Detection

Abstract

With the range of photo manipulation tools now available nearly anyone can modify and change an image's interpretation by vast degree. An image can be called as a chronicle of visual perception. Copying and pasting a patch of an image on to other part in the same image is the main essence of a copy- move forgery and can be employed for many malicious purposes. Malicious image manipulations are inimical as they can lead to serious changes to the information that is perceived by the human mind. Many techniques to detect copy-move image forgery using feature descriptors have been used in the past. SIFT features are considered as a robust scale, rotation, translation and affine invariant feature. We have used the approach of clustering similar SIFT feature descriptors and propose to extend the copy move region detection by introduction of segmentation mechanism for precise detection of the forged region.