Search results for "Image forensics"

showing 7 items of 7 documents

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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Copy–Move Forgery Detection by Matching Triangles of Keypoints

2015

Copy-move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to find similar areas. In this paper, we present a very novel hybrid approach, which compares triangles rather than blocks, or single points. Interest points are extracted from the image, and objects are modeled as a set of connected triangles built onto these points. Triangles are matched according to their shapes (inner angles), their content (c…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer Networks and CommunicationsComputer scienceDelaunay triangulationbusiness.industryFeature vectorSURFFeature extractionScale-invariant feature transformPattern recognitionDelaunay TriangulationDigital Image ForensicVisualizationVertex (geometry)Copy-move ForgeryDigital imageComputer Networks and CommunicationHarriSIFTComputer visionArtificial intelligenceSafety Risk Reliability and QualitybusinessCopy-move Forgery; Delaunay Triangulation; Digital Image Forensics; Harris; SIFT; SURF; Computer Networks and Communications; Safety Risk Reliability and QualityTransformation geometryIEEE Transactions on Information Forensics and Security
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A tool to support the creation of datasets of tampered videos

2015

Digital Video Forensics is getting a growing interest from the Multimedia research community, as the need for methods to validate the authenticity of a video content is increasing with the number of videos freely available to the digital users. Unlike Digital Image Forensics, to our knowledge, there are not standard datasets to test video forgery detection techniques. In this paper we present a new tool to support the users in creating datasets of tampered videos. We furthermore present our own dataset and we discuss some remarks about how to create forgeries difficult to be detected by an observer, to the naked eye.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCopy move forgeryCopy move forgeryInformation retrievalVideo forensicComputer scienceForgery detectionComputer Science (all)Digital videoComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObject trackingCopy move forgery; Object tracking; Video forensics; Computer Science (all); Theoretical Computer ScienceData scienceTheoretical Computer ScienceVideo trackingResearch communityDigital image forensics
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Copy-move Forgery Detection via Texture Description

2010

Copy-move forgery is one of the most common type of tampering in digital images. Copy-moves are parts of the image that are copied and pasted onto another part of the same image. Detection methods in general use block-matching methods, which first divide the image into overlapping blocks and then extract features from each block, assuming similar blocks will yield similar features. In this paper we present a block-based approach which exploits texture as feature to be extracted from blocks. Our goal is to study if texture is well suited for the specific application, and to compare performance of several texture descriptors. Tests have been made on both uncompressed and JPEG compressed image…

Texture compressionComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage forensicscomputer.file_formatTexture (music)JPEGUncompressed videoDigital imageImage textureBlock (programming)Feature (computer vision)Computer visionArtificial intelligencebusinesscomputer
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Detection of Duplicated Regions in Tampered Digital Images by Bit-Plane Analysis

2009

In this paper we present a new method for searching duplicated areas in a digital image. The goal is to detect if an image has been tampered by a copy-move process. Our method works within a convenient domain. The image to be analyzed is decomposed in its bit-plane representation. Then, for each bitplane, block of bits are encoded with an ASCII code, and a sequence of strings is analyzed rather than the original bit-plane. The sequence is lexicographically sorted and similar groups of bits are extracted as candidate areas, and passed to the following plane to be processed. Output of the last planes indicates if, and where, the image has been altered.

business.industryComputer scienceBinary imageImage processingImage Forensics Image Analysis Bit-Plane Decomposition Duplication Detection Image ForgeriesPlane (Unicode)Digital imageDigital image processingComputer visionArtificial intelligencebusinessBlock (data storage)Feature detection (computer vision)Bit plane
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Tekniikoita digitaalisten valokuvien aitouden arvioimiseen

2009

 Ollari, Ilkka Tietojärjestelmätieteen kandidaatintutkielma / Ilkka Ollari Jyväskylä: Jyväskylän yliopisto, 2009, 28 s. Kandidaatintutkielma Digitaalisten valokuvien muokkaamisesta on tullut hyvin helppoa ja yleistä, mikä on osaltaan johtanut valokuvien luotettavuuden heikentymiseen. Tässä tutkielmassa käsittelen kirjallisuuskatsauksen pohjalta erilaisia valokuvien aitouden arvioimiseen tarkoitettuja tekniikoita. Tutkin mm. sitä, kuinka luotettavasti kyseisillä tekniikoilla valokuvien aitous voidaan varmistaa, ja minkälaisia rajoitteita eri tekniikoilla on. Tekniikat voidaan jakaa aktiivisiin ja passiivisiin. Ensin mainitusta ryhmästä käsittelen vesileimoja, jotka ovat merkittävin aktiivist…

vesileimadigital image forensicskuvan muokkausdigitaalisten valokuvien autentikointi
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Digitaalisten kuvaväärennösten tunnistaminen JPEG-pakkausta hyödyntäen

2010

Digitaalisten valokuvien muokkaamisesta on tullut hyvin helppoa ja yleistä, mikä on nostanut esille huolen valokuvien uskottavuudesta. Ongelman ratkaisuksi on esitetty erilaisia tekniikoita, joilla valokuvien aitoutta voidaan arvioida. Tarkastelen tässä tutkielmassa niin sanottuja passiivisia tekniikoita, jotka eivät edellytä kuvasta minkäänlaista ennakkotietoa, kuten vesileimaa. Vertailen viittä tällaista tekniikkaa laatimani neljä kohtaa käsittävän kriteeristön pohjalta. Vertailtavia ominaisuuksia ovat tarkkuus, tunnistetut muokkaustyypit, rajoitukset sekä vakaus vastatoimia vastaan. Vertailu osoittaa, että eräs merkittävimmistä tekniikoiden ongelmista on niiden huono toleranssi kuvan häv…

väärennöksettodentaminendigitaalikuvausJPEGdigital image forensicskuvankäsittelykuvat
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