This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics applications.
PRNU pattern alignment for images and videos based on scene content / Bellavia Fabio, Iuliani Massimo, Fanfani Marco, Colombo Carlo, Piva Alessandro. - ELETTRONICO. - (2019), pp. 0-0. (Intervento presentato al convegno 26th International Conference on Image Processing ICIP 2019 tenutosi a Taipei, Taiwan nel September 2-5, 2019) [10.1109/ICIP.2019.8802990].
PRNU pattern alignment for images and videos based on scene content
Bellavia Fabio
;Iuliani Massimo;Fanfani Marco;Colombo Carlo;Piva Alessandro
2019
Abstract
This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics applications.File | Dimensione | Formato | |
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