Prnu Pattern Alignment for Images and Videos Based on Scene Content

Fabio Bellavia, Bellavia, Marco Fanfani, Massimo Iuliani, Alessandro Piva, Carlo Colombo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

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
Original languageEnglish
Title of host publication2019 IEEEInternational Conferenceon Image Processing - Proceedings
Pages91-95
Number of pages5
Publication statusPublished - 2019

Publication series

NamePROCEEDINGS - INTERNATIONAL CONFERENCE ON IMAGE PROCESSING

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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