Research Article A Feature-Based Forensic Procedure for Splicing Forgeries Detection Irene Amerini, 1 Rudy Becarelli, 1 Roberto Caldelli, 1,2 and Matteo Casini 1 1 Media Integration and Communication Center (MICC), Universit` a degli Studi di Firenze, 50134 Firenze, Italy 2 National Interuniversity Consortium for Telecommunications (CNIT), 43124 Parma, Italy Correspondence should be addressed to Roberto Caldelli; roberto.caldelli@unif.it Received 4 June 2015; Revised 11 November 2015; Accepted 20 December 2015 Academic Editor: Fazal M. Mahomed Copyright © 2015 Irene Amerini et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Nowadays, determining if an image appeared somewhere on the web or in a magazine or is authentic or not has become crucial. Image forensics methods based on features have demonstrated so far to be very efective in detecting forgeries in which a portion of an image is cloned somewhere else onto the same image. Anyway such techniques cannot be adopted to deal with splicing attack, that is, when the image portion comes from another picture that then, usually, is not available anymore for an operation of feature match. In this paper, a procedure in which these techniques could also be employed will be shown to get rid of splicing attack by resorting to the use of some repositories of images available on the Internet like Google Images or TinEye Reverse Image Search. Experimental results are presented on some real case images retrieved on the Internet to demonstrate the capacity of the proposed procedure. 1. Introduction When looking at a digital image, it is quite common to wonder if it is original or has been counterfeited in some way. Such a doubt is basically determined by the easiness with which digital images can be manipulated to change their content and especially their visual meaning. Te contexts where doctored pictures could be involved are very disparate; they could be used in a tabloid or in an advertising poster or included in a journalistic report but also in a court of law where digital (sometimes printed) images are presented as crucial evidences for a trial in order to infuence the fnal judgement. So, especially in the last case, reliably assessing image integrity becomes of fundamental importance. Image forensics specifcally deals with such issues by studying and developing technological tools which generally permit determining, by only analyzing a digital photograph (i.e., its pixels), if that asset has been manipulated or even which could have been the adopted acquisition device (such an issue is not relevant to the topic of the present paper). Moreover, if it has been established that something has been altered, it could be important to understand in which part of the image itself such a modifcation occurred, for instance, if a person or a specifc object has been covered, if an area of the image has been cloned, if something (i.e., a face or a weapon) has been copied from another diferent image, or, even more, ifa mixture of these processes has been carried out. Among the diferent attacks that can be carried out to modify an image, two are surely the most important. Te frst one is the splicing attack which is performed when a portion of an image has been cut out and, afer having been adapted (e.g., zoomed in or out, fltered), is inserted into another one to build a new “fake image.” Te second one is the copy-move attack which is basically a splicing attack but what is crucial is that the clipped image portion is pasted somewhere else within the same image. On the other side, regarding forgeries individuation, three are the principal classes of detectors studied so far: those based on double JPEG compression [1–3] adopted to reveal splicing attack, those based on inconsistent shadows [4], and fnally those based on local features descriptors (mainly SIFT—Scale Invariant Feature Transform) [5–8] usually used to get rid of copy-move attack. A complete overview of forensic methods for tampering detection is well introduced in [9]. In particular, features-based methods (based on SIFT Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2015, Article ID 653164, 6 pages http://dx.doi.org/10.1155/2015/653164