{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/detection-of-copy-move-forgery-in-digital","title":"Detection of copy-move forgery in digital images based on DCT","arxiv_id":"1308.5661","date":"2013-08-26","proceeding":null,"authors":["Nathalie Diane Wandji","Sun Xingming","Moise Fah Kue"],"abstract":"With rapid advances in digital information processing systems, and more\nspecifically in digital image processing software, there is a widespread\ndevelopment of advanced tools and techniques for digital image forgery. One of\nthe techniques most commonly used is the Copy-move forgery which proceeds by\ncopying a part of an image and pasting it into the same image, in order to\nmaliciously hide an object or a region. In this paper, we propose a method to\ndetect this specific kind of counterfeit. Firstly, the color image is converted\nfrom RGB color space to YCbCr color space and then the R, G, B and Y-component\nare splitted into fixed-size overlapping blocks and, features are extracted\nfrom the R, G and B-components image blocks on one hand and on the other, from\nthe DCT representation of the R, G, B and Ycomponent image block. The feature\nvectors obtained are then lexicographically sorted to make similar image blocks\nneighbors and duplicated image blocks are identified using Euclidean distance\nas similarity criterion. Experimental results showed that the proposed method\ncan detect the duplicated regions when there is more than one copy move forged\narea in the image and even in case of slight rotations, JPEG compression,\nshift, scale, blur and noise addition.","url_abs":"http://arxiv.org/abs/1308.5661v1","url_pdf":"http://arxiv.org/pdf/1308.5661v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"detection-of-copy-move-forgery-in-digital","repo_url":"https://github.com/esimov/forensic","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}