15 March 2018 Copy–move forgery detection utilizing Fourier–Mellin transform log-polar features
Rahul Dixit, Ruchira Naskar
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Abstract
In this work, we address the problem of region duplication or copy–move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier–Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy–move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Rahul Dixit and Ruchira Naskar "Copy–move forgery detection utilizing Fourier–Mellin transform log-polar features," Journal of Electronic Imaging 27(2), 023007 (15 March 2018). https://doi.org/10.1117/1.JEI.27.2.023007
Received: 11 October 2017; Accepted: 20 February 2018; Published: 15 March 2018
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Cited by 7 scholarly publications.
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KEYWORDS
Image segmentation

RGB color model

Feature extraction

Databases

Detection and tracking algorithms

Expectation maximization algorithms

Discrete wavelet transforms

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