Detection of Copy-Scale-Move Forgery in Digital Images Using SFOP and MROGH
Social network platforms such as Twitter, Instagram and Facebook are one of the fastest and most convenient means for sharing digital images. Digital images are generally accepted as credible news but, it may undergo some manipulations before being shared without leaving any obvious traces of tampering; due to existence of the powerful image editing softwares. Copy-move forgery technique is a very simple and common type of image forgery, where a part of the image is copied and then pasted in the same image to replicate or hide some parts from the image. In this paper, we proposed a copy-scale-move forgery detection method based on Scale Invariant Feature Operator (SFOP) detector. The keypoints are then described using MROGH descriptor. Experimental results show that the proposed method is able to locate and detect the forgery even if under some geometric transformations such as scaling.
KeywordsImage forensics Copy-move Forgery detection Scale invariant feature RANSAC MROGH descriptor
The authors would like to thank all anonymous reviewers for their insightful comments. Additionally, This work is supported by the National Natural Science Foundation of China (Grant Number: 61471141, 61301099, 61361166006), the Fundamental Research Funds for the Central Universities (Grant Number: HIT. KISTP. 201416, HIT. KISTP. 201414).
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