1,721,127 research outputs found
Compressione dei dati SAR grezzi mediante focalizzazione in range e codifica a tasso variabile
Tesi di Dottorat
Media Forensics and DeepFakes: an overview
With the rapid progress of recent years, techniques that generate and
manipulate multimedia content can now guarantee a very advanced level of
realism. The boundary between real and synthetic media has become very thin. On
the one hand, this opens the door to a series of exciting applications in
different fields such as creative arts, advertising, film production, video
games. On the other hand, it poses enormous security threats. Software packages
freely available on the web allow any individual, without special skills, to
create very realistic fake images and videos. So-called deepfakes can be used
to manipulate public opinion during elections, commit fraud, discredit or
blackmail people. Potential abuses are limited only by human imagination.
Therefore, there is an urgent need for automated tools capable of detecting
false multimedia content and avoiding the spread of dangerous false
information. This review paper aims to present an analysis of the methods for
visual media integrity verification, that is, the detection of manipulated
images and videos. Special emphasis will be placed on the emerging phenomenon
of deepfakes and, from the point of view of the forensic analyst, on modern
data-driven forensic methods. The analysis will help to highlight the limits of
current forensic tools, the most relevant issues, the upcoming challenges, and
suggest future directions for research
Compressione dei dati SAR grezzi mediante focalizzazione in range e codifica a tasso variabile
Tesi di Dottorat
Design of low-resolution multiple description vector quantizers by means of the self organizing maps
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 200
Image forgery localization through the fusion of camera-based, feature-based and pixel-based techniques
Compression of SAR raw data through range focusing and variable-rate trellis-coded quantization
Iris liveness detection for mobile devices based on local descriptors
Iris recognition is well suited to authentication on mobile devices, due to its intrinsic security and non-intrusiveness. However, authentication systems can be easily tricked by attacks based on high-quality printing. A liveness detection module is therefore necessary. Here, we propose a fast and accurate technique to detect printed-iris attacks based on the local binary pattern (LBP) descriptor. In order to improve the discrimination ability of LBP and better explore the image statistics, LBP is performed on a high-pass version of the image with 3 × 3 integer kernel. In addition a simplified interpolation-free descriptor is considered and finally a linear SVM classification scheme is used. The detection performance, measured on standard databases, is extremely promising, despite the resulting very low complexity, which makes possible the implementation for the relatively small CPU processing power of a mobile device
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