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Copy Move Forgery Detection on Digital Images

by Ruchita Singh, Ashish Oberoi, Nishi Goel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 9
Year of Publication: 2014
Authors: Ruchita Singh, Ashish Oberoi, Nishi Goel

Ruchita Singh, Ashish Oberoi, Nishi Goel . Copy Move Forgery Detection on Digital Images. International Journal of Computer Applications. 98, 9 ( July 2014), 17-22. DOI=10.5120/17211-7437

@article{ 10.5120/17211-7437,
author = { Ruchita Singh, Ashish Oberoi, Nishi Goel },
title = { Copy Move Forgery Detection on Digital Images },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 9 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { },
doi = { 10.5120/17211-7437 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:25:45.759641+05:30
%A Ruchita Singh
%A Ashish Oberoi
%A Nishi Goel
%T Copy Move Forgery Detection on Digital Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 9
%P 17-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

In today's scenario forging of the Digital images has become a common phenomena. The availability of low cost manipulation software also boost to this practice. The foremost practice of manipulating the digital images employed by the most forgerer is the copy move forgery. Copy move forgery is basically concerned with concealing or duplicating one region in an image by pasting certain portions of the same image on it. Numerous Algorithms are proposed to detect copy move forgery in digital images. In this paper an enhanced way to detect copy move forgery is proposed. It is analyzed that block based methods are secured against noise and JPEG compression where as feature based methods are robust to the rotation and scaling operations . The proposed approach use both block based method and feature based method to increase the accuracy rate of forgery detection. The Proposed method employed DCT and SIFT to extract features from image and matching those collected features to detect forgery on image and also perform the localization of the Forged Regions in the Digital Image.

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Index Terms

Computer Science
Information Sciences


Forgery DCT SIFT Copy-Move Block-Based Method Feature-Based Method.