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Prnu Pattern Alignment for Images and Videos Based on Scene Content

2019

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 ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni021110 strategic defence & security studiesSettore INF/01 - Informaticabusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesPRNU SIFT image registration video stabilizationParticle swarm optimization02 engineering and technologyVideos Particle swarm optimization Image resolution Correlation Reliability Cameras SensorsIdentification (information)Content (measure theory)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessReliability (statistics)
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