Copy-move forgery detection technique based on discrete cosine transform blocks features
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S.I. : HIGHER LEVEL ARTIFICIAL NEURAL NETWORK BASED INTELLIGENT SYSTEMS
Copy-move forgery detection technique based on discrete cosine transform blocks features Esteban Alejandro Armas Vega1 • Edgar Gonza´lez Ferna´ndez1 • Ana Lucila Sandoval Orozco1 Luis Javier Garcı´a Villalba1
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Received: 1 September 2020 / Accepted: 7 October 2020 Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract With the increasing number of software applications that allow altering digital images and their ease of use, they weaken the credibility of an image. This problem, together with the ease of distributing information through the Internet (blogs, social networks, etc.), has led to a tendency for information to be accepted as true without its veracity being questioned. Image counterfeiting has become a major threat to the credibility of the information. To deal with this threat, forensic image analysis is aimed at detecting and locating image forgeries using multiple clues that allows it to determine the veracity or otherwise of an image. In this paper, we present a method for the authentication of images. The proposed method performs detection of copy-move alterations within an image, using the discrete cosine transform. The characteristics obtained from these coefficients allow us to obtain transfer vectors, which are grouped together. Through the use of a tolerance threshold, it is possible to determine whether there are regions copied and pasted within the analysed image. The results obtained from the experiments reported in this paper demonstrate the effectiveness of the proposed method. For the evaluation of the proposed methods, experiments were carried out with public databases of falsified images that are widely used in the literature. Keywords Cope-move forgery Digital images Discrete cosine transforms Forgery detection
1 Introduction
& Luis Javier Garcı´a Villalba [email protected] Esteban Alejandro Armas Vega [email protected] Edgar Gonza´lez Ferna´ndez [email protected] Ana Lucila Sandoval Orozco [email protected] 1
Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor Jose´ Garcı´a Santesmases, 9, Ciudad Universitaria, 28040 Madrid, Spain
As the famous saying goes, ‘‘A picture is worth a thousand words’’ and this has never been more true than in today’s visually oriented society. Currently, images are used in many common areas such as teaching, journalism, jurisprudence, medicine, advertising, art, etc. Driven by social media networks and instant messaging applications, multimedia content is the primary source of internet traffic. Besides all of this, the continuous improvement of the cameras incorporated in mobile devices together with the evolution of the image editing tools has made it easier to manipulate an image with excellent results and shared it with the world th
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