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RESEARCH PRODUCT
State of the art in passive digital image forgery detection: copy-move image forgery
Sajjad DadkhahSomayeh SadeghiDiaa M. UliyanHamid A. JalabGiuseppe Mazzolasubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCopyingCopy-move forgery Digital forensics Duplicated detection Manipulation detectionbusiness.industryComputer sciencemedia_common.quotation_subjectDigital forensicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineering02 engineering and technologyImage (mathematics)Digital imageArtificial IntelligenceOriginalityPattern recognition (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionRelevance (information retrieval)Computer Vision and Pattern RecognitionArtificial intelligenceState (computer science)businessmedia_commondescription
Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is copy-move digital image forgery, which involves copying one part of the image onto another area of the same image. Various methods have been proposed to detect copy-move forgery that uses different types of transformations. The goal of this paper is to determine which copy-move forgery detection methods are best for different image attributes such as JPEG compression, scaling, rotation. The advantages and drawbacks of each method are also highlighted. Thus, the current state-of-the-art image forgery detection techniques are discussed along with their advantages and drawbacks.
year | journal | country | edition | language |
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2017-12-26 | Pattern Analysis and Applications |