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

Bellavia, F., Iuliani, M., Fanfani, M., Colombo, C., Piva, A. (2019). Prnu Pattern Alignment for Images and Videos Based on Scene Content. In 2019 IEEEInternational Conferenceon Image Processing - Proceedings (pp. 91-95). The Institute of Electrical and Electronics Engineers, IEEE [10.1109/ICIP.2019.8802990].

Prnu Pattern Alignment for Images and Videos Based on Scene Content

Bellavia, F.;
2019-01-01

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
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
978-1-5386-6249-6
Bellavia, F., Iuliani, M., Fanfani, M., Colombo, C., Piva, A. (2019). Prnu Pattern Alignment for Images and Videos Based on Scene Content. In 2019 IEEEInternational Conferenceon Image Processing - Proceedings (pp. 91-95). The Institute of Electrical and Electronics Engineers, IEEE [10.1109/ICIP.2019.8802990].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/385503
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