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Computer Optics, 2017, Volume 41, Issue 1, Pages 79–87 (Mi co360)  

IMAGE PROCESSING, PATTERN RECOGNITION

Local patterns in the copy-move detection problem solution

N. I. Evdokimovaa, A. V. Kuznetsovab

a Samara National Research University, Samara, Russia
b Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia

Abstract: Embedding of duplicates is one of commonly used methods of image forgery. During this process, an image fragment is copied and pasted to another position in the same image. This is performed to conceal some important part of the image. A copy-move forgery detection algorithm aims to recognize duplicated areas in the image. This algorithm is based on calculating the characteristics in a sliding or overlapping window. In this paper, we compare the performance of copymove detection algorithms that utilize a local binary pattern, a local ternary pattern, a local derivative pattern, and some extensions thereof. A distinctive feature of the used characteristics is their resistance to distortions inserted into the copy, such as linear contrast enhancement and impulse noise. This method also has low computational complexity.

Keywords: copy-move, forgery, local binary pattern, local ternary pattern, local derivative pattern.

Funding Agency Grant Number
Russian Foundation for Basic Research 16-37-00056-мол_а
The work was partially funded by the RFBR grant No. 16-37-00056.


DOI: https://doi.org/10.18287/2412-6179-2017-41-1-79-87

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Full text: http://www.computeroptics.smr.ru/.../410109.html
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Received: 12.12.2016
Accepted:20.01.2017

Citation: N. I. Evdokimova, A. V. Kuznetsov, “Local patterns in the copy-move detection problem solution”, Computer Optics, 41:1 (2017), 79–87

Citation in format AMSBIB
\Bibitem{EvdKuz17}
\by N.~I.~Evdokimova, A.~V.~Kuznetsov
\paper Local patterns in the copy-move detection problem solution
\jour Computer Optics
\yr 2017
\vol 41
\issue 1
\pages 79--87
\mathnet{http://mi.mathnet.ru/co360}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-1-79-87}


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