Abstract: Copy-move forgeries are parts of the image that are duplicated elsewhere into the same image, often after being modified by geometrical transformations. In this paper we present a method to detect these image alterations, using a SIFT-based approach. First we describe a state of the art SIFT-point matching method, which inspired our algorithm, then we compare it with our SIFT-based approach, which consists of three parts: keypoint clustering, cluster matching, and texture analysis. The goal is to find copies of the same object, i.e. clusters of points, rather than points that match. Cluster matching proves to give better results than single point matching, since it returns a complete and coherent comparison between copied objects. At last, textures of matching areas are analyzed and compared to validate results and to eliminate

  url          = {http://gitl.sysu.edu.cn/papers/icip2010/pdfs/0002117.pdf},
  booktitle    = {International Conference on Image Processing},
  author       = {Edoardo Ardizzone and Alessandro Bruno and Giuseppe Mazzola},
  location     = {Hong Kong},
  year         = {2010},
  title        = {Detecting multiple copies in tampered images},