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Reseach Article

Copy-Move Forgery Detection using Orthogonal Wavelet Transforms

by Tanuja K. Sarode, Naveen Vaswani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 88 - Number 8
Year of Publication: 2014
Authors: Tanuja K. Sarode, Naveen Vaswani
10.5120/15375-3966

Tanuja K. Sarode, Naveen Vaswani . Copy-Move Forgery Detection using Orthogonal Wavelet Transforms. International Journal of Computer Applications. 88, 8 ( February 2014), 41-45. DOI=10.5120/15375-3966

@article{ 10.5120/15375-3966,
author = { Tanuja K. Sarode, Naveen Vaswani },
title = { Copy-Move Forgery Detection using Orthogonal Wavelet Transforms },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 88 },
number = { 8 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume88/number8/15375-3966/ },
doi = { 10.5120/15375-3966 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:07:07.792640+05:30
%A Tanuja K. Sarode
%A Naveen Vaswani
%T Copy-Move Forgery Detection using Orthogonal Wavelet Transforms
%J International Journal of Computer Applications
%@ 0975-8887
%V 88
%N 8
%P 41-45
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the help of various image editing tools available, it has become easier to alter an image in such a way that it does not leave behind any clues. Copy –Move forgery is a type of image forgery in which a part of digital image is copied and pasted to another part of same image. Since the copied and pasted image comes from the same image, it becomes difficult to detect the forgery. Generally the intention behind Copy-Move forgery is to hide important objects in an image. In this paper, an orthogonal wavelet transform based forgery detection method is proposed. Orthogonal wavelet transform is generated from basic orthogonal transforms. We consider generating Discrete Cosine Transform Wavelet (DCTW) transform and Walsh Wavelet (WW) transform from DCT and Walsh orthogonal transforms. The image is divided into overlapping blocks. On each block, DCTW and WW transforms are applied. From each block discriminative features are extracted from coefficients. These feature vectors are lexicographically sorted and block matching step is applied to find duplicated blocks.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Copy –Move Forgery Copy –Move Attack Discrete Cosine Transform Walsh Transform Orthogonal Transforms Wavelet Transforms