0000000000516053

AUTHOR

Massimo Iuliani

showing 3 related works from this author

A vision-based fully automated approach to robust image cropping detection

2020

Abstract The definition of valid and robust methodologies for assessing the authenticity of digital information is nowadays critical to contrast social manipulation through the media. A key research topic in multimedia forensics is the development of methods for detecting tampered content in large image collections without any human intervention. This paper introduces AMARCORD (Automatic Manhattan-scene AsymmetRically CrOpped imageRy Detector), a fully automated detector for exposing evidences of asymmetrical image cropping on Manhattan-World scenes. The proposed solution estimates and exploits the camera principal point, i.e., a physical feature extracted directly from the image content th…

Robust computer visionExploitComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRobust statisticsImage processing02 engineering and technologyCropping detectionMultimedia forensicRobustness (computer science)0202 electrical engineering electronic engineering information engineeringMultimedia Forensics Robust Computer Vision Cropping Detection Image Content AnalysisComputer visionElectrical and Electronic EngineeringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaVision basedbusiness.industryDetectorImage content analysi020206 networking & telecommunicationsFully automatedSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessCroppingSoftwareSignal Processing: Image Communication
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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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FISH: Face Intensity-Shape Histogram representation for automatic face splicing detection

2019

Abstract Tampered images spread nowadays over any visual media influencing our judgement in many aspects of our life. This is particularly critical for face splicing manipulations, where recognizable identities are put out of context. To contrast these activities on a large scale, automatic detectors are required. In this paper, we present a novel method for automatic face splicing detection, based on computer vision, that exploits inconsistencies in the lighting environment estimated from different faces in the scene. Differently from previous approaches, we do not rely on an ideal mathematical model of the lighting environment. Instead, our solution, built upon the concept of histogram-ba…

ExploitComputer scienceLighting environmentContext (language use)02 engineering and technologyImage Forensics Scene level analysis Geometric Constraints Lighting environment Face splicing detectionHistogram0202 electrical engineering electronic engineering information engineeringMedia TechnologyComputer visionElectrical and Electronic EngineeringRepresentation (mathematics)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniIdeal (set theory)Scene level analysisSettore INF/01 - Informaticabusiness.industryImage forensicContrast (statistics)020207 software engineeringGeometric constraintFace (geometry)Signal Processing020201 artificial intelligence & image processingFace splicing detectionComputer Vision and Pattern RecognitionArtificial intelligencebusinessScale (map)
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