Sandoval Orozco, Ana Lucila, Corripio, Jocelin Rosales, García Villalba, Luis Javier, Hernandez-Castro, Julio C. (2015) Image source acquisition identification of mobile devices based on the use of features. Multimedia Tools and Applications, 75 (12). pp. 7087-7111. ISSN 1380-7501. E-ISSN 1573-7721. (doi:10.1007/s11042-015-2633-2) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:61966)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: https://doi.org/10.1007/s11042-015-2633-2 |
Abstract
Nowadays, forensic analysis of digital images is especially important, given the frequent use of digital cameras in mobile devices. The identification of the device type or the make and model of image source are two important branches of forensic analysis of digital images. In this paper we have addressed both of these, with an approach based on different types of image features and the classification using support vector machines. The study has mainly focused on images created with mobile devices and as a result, the techniques and features have been adapted or created for this purpose. There have been a total of 36 experiments classified into 5 sets, in order to test different configurations of the techniques. In the configuration of the experiments, the future use of the technique by the forensic analyst in real situations to create experiments with high technical requirements was taken into account, amongst other things.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s11042-015-2633-2 |
Uncontrolled keywords: | Forensics analysis, Counter forensics, Image anonymity, Image forgery, Photo response non, uniformity Wavelet |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Julio Hernandez Castro |
Date Deposited: | 06 Jun 2017 13:15 UTC |
Last Modified: | 05 Nov 2024 10:56 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/61966 (The current URI for this page, for reference purposes) |
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