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.

A Forensic Tool for Investigating Image Forgeries / Marco, Fontani; Bianchi, Tiziano; Alessia De, Rosa; Alessandro, Piva; Mauro, Barni. - In: INTERNATIONAL JOURNAL OF DIGITAL CRIME AND FORENSICS. - ISSN 1941-6210. - 5:4(2013), pp. 15-33. [10.4018/ijdcf.2013100102]

A Forensic Tool for Investigating Image Forgeries

BIANCHI, TIZIANO;
2013

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2537288
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