The Forensic Science (sometimes shortened to Forensics) is the application of technical and scientific methods to the justice, investigation and evidence discovery domain. Specifically finding evidences can be trivial and in many fields is achieved with methods that exploits manual processes and the experience of the forensics examiner. Though human factor can be often discussed and the evidences collected and found without repeatable and scientific methods could be of no use in tribunal. For these reasons this thesis focus on the investigation and development of classification engine able to uniquely identify and classify evidences in a scientific and repeatable way: each decision is driven by features and is associated by a confidence number that is the evidence itself. Two application in two different domains of Ballistics will be described: Image Ballistics, that is the reconstruction of the history of an image, and Fire Weapon Ballistics, that is the identification of the Weapon that fired an investigated bullet from the imprintings left on the bullet cartridge. To understand how to solve these two real in-the-field problems, multimedia-based novel techniques will be presented with promising results both in Image and Classic Ballistics domain.
Digital Forensics Ballistics: Reconstructing the source of an evidence exploiting multimedia data / Giudice, Oliver. - (2017 Jul 31).
Digital Forensics Ballistics: Reconstructing the source of an evidence exploiting multimedia data
GIUDICE, OLIVER
2017-07-31
Abstract
The Forensic Science (sometimes shortened to Forensics) is the application of technical and scientific methods to the justice, investigation and evidence discovery domain. Specifically finding evidences can be trivial and in many fields is achieved with methods that exploits manual processes and the experience of the forensics examiner. Though human factor can be often discussed and the evidences collected and found without repeatable and scientific methods could be of no use in tribunal. For these reasons this thesis focus on the investigation and development of classification engine able to uniquely identify and classify evidences in a scientific and repeatable way: each decision is driven by features and is associated by a confidence number that is the evidence itself. Two application in two different domains of Ballistics will be described: Image Ballistics, that is the reconstruction of the history of an image, and Fire Weapon Ballistics, that is the identification of the Weapon that fired an investigated bullet from the imprintings left on the bullet cartridge. To understand how to solve these two real in-the-field problems, multimedia-based novel techniques will be presented with promising results both in Image and Classic Ballistics domain.File | Dimensione | Formato | |
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