Uliyan, D.M. and Jalab, H.A. and Wahab, A.W.A. and Shivakumara, P. and Sadeghi, S. (2016) A novel forged blurred region detection system for image forensic applications. Expert Systems with Applications, 64. pp. 1-10. ISSN 0957-4174, DOI https://doi.org/10.1016/j.eswa.2016.07.026.
Full text not available from this repository.Abstract
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.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Blurred forged region detection; Copy–move detection; Feature similarity; Phase congruency; Statistical features; Structural features |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 25 Aug 2017 01:35 |
| Last Modified: | 25 Aug 2017 01:35 |
| URI: | http://eprints.um.edu.my/id/eprint/17719 |
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