The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Forensic Tool for Investigating Image Forgeries
|
|
Author(s): Marco Fontani (Department of Information Engineering and Mathematical Sciences, University of Siena, Siena, Italy), Tiziano Bianchi (Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy), Alessia De Rosa (National Inter-University Consortium for Telecommunications, University of Florence, Firenze, Italy), Alessandro Piva (Department of Information Engineering, University of Florence, Firenze, Italy)and Mauro Barni (Department of Information Engineering and Mathematical Sciences, University of Siena, Siena, Italy)
Copyright: 2013
Volume: 5
Issue: 4
Pages: 19
Source title:
International Journal of Digital Crime and Forensics (IJDCF)
Editor(s)-in-Chief: Feng Liu (Chinese Academy of Sciences, China)
DOI: 10.4018/ijdcf.2013100102
Purchase
|
Abstract
Images have always been considered a reliable source of evidence in the past. Today, the wide availability of photo editing software urges the authors to investigate the origin and the integrity of a digital image before trusting it. Although several algorithms have been developed for image integrity verification, a comprehensive tool that allows the analyst to synergically exploit these algorithms, and to reach a final decision based on their output, is still lacking. In this work the authors propose an image forensic tool trying to fill this gap. The proposed tool exploits state of the art algorithms for splicing detection, with forgery localization capabilities, and make them available to the analyst through a graphical interface. In order to help the analyst in reaching a final assessment, a decision fusion engine is employed to intelligently merge the output of different algorithms, boosting detection performance. The tool has a modular architecture, that makes it easily scalable.
Related Content
|
Shakir A. Mehdiyev, Tahmasib Kh. Fataliyev.
© 2024.
17 pages.
|
|
Fuhai Jia, Yanru Jia, Jing Li, Zhenghui Liu.
© 2024.
13 pages.
|
|
Dawei Zhang.
© 2024.
16 pages.
|
|
Yuwen Zhu, Lei Yu.
© 2023.
16 pages.
|
|
Vijay Kumar, Sahil Sharma, Chandan Kumar, Aditya Kumar Sahu.
© 2023.
14 pages.
|
|
Wenjun Yao, Ying Jiang, Yang Yang.
© 2023.
20 pages.
|
|
Dawei Zhang.
© 2023.
14 pages.
|
|
|