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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Blur Invariant Image Forgery Detection Method Using Local Phase Quantization
Author(s)
Beste Ustubioglu, Elif Baykal, Gul Muzaffer and Guzin Ulutas
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DOI:10.17265/1934-8975/2016.06.004
Affiliation(s)
Department of Computer Engineering, Karadeniz Technical University, Trabzon 61080, Turkey
ABSTRACT
With
the rapid development of powerful image, editing software makes the forgery of the digital image easy. Researchers
proposed methods to cope with image authentication in recent years. We proposed
a passive image authentication technique to determine the copy move forgery that
copied a part of an image and pasted it on the other region in the same image. First, the method divides the image
into overlapping blocks. It uses LPQ (local phase quantization) to label each block.
The column average value of labeled blocks constitutes the feature vector for the
block. Similarity among the feature vectors gives a clue about the forgery. Local
phase quantization has not been used to detect copy move forgery in the literature
before. Experimental results show that, the method has higher accuracy ratios and lower false negative values under
blurring operation at high levels compared to other methods. Our method can also
detect multiple copy move forgery.
KEYWORDS
Copy move forgery, LPQ, blur invariant.
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