Deep features for image copy move forgery detection

Abstract

In this modern era, there has been a increase in the copying and moving of illegalities, distributing them, and then tempered images. These days even the most secured data sometimes go under devastating forgery. Copy forgery is seen to be the easiest copying method without leaving any obvious traces of manipulating an image’s content.Like working on the pixels of an image by geometrical and illumination techniques which are either cut or copied or copied to some other place of the identical image. In this paper, we propose copy paste forgery detection of an image by extracting and grouping SIFT key points for analyzation. The first step is to find suspicious clusters of key points and patches to roughly estimate the dimensionality of SIFT. Secondly, it finds pixel level, scale, and color by comparingsimilar neighborhoods of matching duplicated regions. The results prove to be giving good performance scores, computational timing, and complexity