Copy Move Image Forgery Detection Based on Polar Fourier Representation - Volume 8 Number 2 (Apr. 2018) - IJMLC
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General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2018 Vol.8(2): 158-163 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.2.680

Copy Move Image Forgery Detection Based on Polar Fourier Representation

Yitian Wang and Sei-ichiro Kamata
Abstract—With the rapid development of multimedia technology, it's easy for someone to obtain an image and edit it according to their own preferences or some ulterior purpose. Copy–Move is a common type of digital image forgery where a part of the original image is copied and pasted at another position in the same image. In this paper, we propose an efficient methodology for enhancing block matching based on Copy–Move forgery detection. The main contribution of this work is the utilization of polar representation to get the representative features for each block. The main feature used in this paper is the frequency of each block based on Fourier transform. The experimental results show the efficiency of the proposed method for detecting copy-move regions, even when the copied region has undergone severe image manipulations such as rotation, scaling, Gaussian blurring, brightness modification, JPEG compression and noise addition.

Index Terms—Copy move, forgery detection, Fourier transform, polar coordinate system.

The authors are with Graduate School of Information, Production and Systems of Waseda university, Kitakyushu, Japan (e-mail: yzwang@,


Cite: Yitian Wang and Sei-ichiro Kamata, "Copy Move Image Forgery Detection Based on Polar Fourier Representation," International Journal of Machine Learning and Computing vol. 8, no. 2, pp. 158-163, 2018.

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