期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 64, 期 -, 页码 1-10出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2016.07.026
关键词
Copy-move detection; Blurred forged region detection; Statistical features; Phase congruency; Structural features; feature similarity
类别
资金
- Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme (FRGS) [FP073-2015A]
As new technologies and devices are introduced in the market, the crime rate also increases in developing and developed countries. One such crime is image forgery which can be detected by forensic applications. In this paper, we propose a novel idea for identifying forgery attack done by blur artifact unlike existing forgery attack done by geometrical distortion such as rotation and scaling. The proposed method segment region of interest from the input forgery image based on the combination of statistical analysis with color texture analysis which includes blur artifact region. For each region of interest, we propose a new method for estimating degree of blur to separate forged blur artifact and normal blur artifact. In order to validate the identified forged blur artifact, we explore Fourier and Gabor texture features to study the structure of the forged blur artifact which eliminates false blur forged blur artifact. To evaluate the proposed forged blurred region detection method, we use two standard databases namely, Image data manipulation, and MICC-F220 for experimentation. Experimental results of the proposed method with existing methods show that the proposed method outperforms the existing methods in terms of forged blur artifact region detection. (C) 2016 Elsevier Ltd. All rights reserved.
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