Reflective SIFT for improving the detection of copy-move image forgery

摘要

Due to technology advancement the digital images are losing authenticity. Because of this different detection techniques are put forward. They check for the Genuinity of the images. We need to take care of image forgery. The images can be scaled, rotated, and flipped (mirror reflected). SIFT (Scale invariant feature transform) is mostly used to match images. But it fails for flipped images. A framework, mirror-reflection invariant feature transform (MIFT) is presented. Here, we will learn how MIFT improvise SIFT. The performance evaluation is demonstrated on various databases such as MICC-F2000 and CASIA V2.0.