To decide whether a digital video has been captured by a given device, multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquired frames. This analysis requires that the noise pattern characterizing the camera and the noise pattern extracted from video frames under analysis are geometrically aligned. However, in many practical scenarios this does not occur, thus a re-alignment or synchronization has to be performed. Current solutions often require time consuming search of the realignment transformation parameters. In this paper, we propose to overcome this limitation by searching scaling and rotation parameters in the frequency domain. The proposed algorithm tested on real videos from a well-known state-of-the-art dataset shows promising results.

A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos

Mandelli S.;Bestagini P.;Tubaro S.
2020-01-01

Abstract

To decide whether a digital video has been captured by a given device, multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquired frames. This analysis requires that the noise pattern characterizing the camera and the noise pattern extracted from video frames under analysis are geometrically aligned. However, in many practical scenarios this does not occur, thus a re-alignment or synchronization has to be performed. Current solutions often require time consuming search of the realignment transformation parameters. In this paper, we propose to overcome this limitation by searching scaling and rotation parameters in the frequency domain. The proposed algorithm tested on real videos from a well-known state-of-the-art dataset shows promising results.
2020
2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
978-1-7281-6395-6
Fourier-Mellin
PRNU
sensor noise
Video forensics
video stabilization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1171200
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