Analysis of image forgery detection algorithms

dc.contributor.advisorDerminder Singh
dc.contributor.authorPriyanka
dc.date.accessioned2019-10-10T04:51:07Z
dc.date.available2019-10-10T04:51:07Z
dc.date.issued2019
dc.description.abstractDigital images are a momentous part of today’s digital communication. It is very easy to manipulate digital images for hiding some useful information by image rendering tools such as Adobe Photoshop, Microsoft Paint etc. The common image forgery which is easy to carry out is copy-move in which some part of an image is copied and pasted on another part of the same image to hide the important information. This study proposes an algorithm to spot the copy-move forgery based on exact match block based technique. The design of interface and development of algorithm have been implemented using GNU Octave 4.2.2 as an IDE and Octave as a programming language. The algorithm works by matching the regions in image that are equivalent by matching the small blocks of size b×b. The program is tested for 45 images of mixed image file formats by considering block sizes 2, 4, 6, 8, 10, 12, 14, and 16. It is observed from the experimental results that the proposed algorithm can detect copy-move image forgery in TIF, BMP and PNG image formats only. Results reveal that as the block size increases, execution time (time taken by CPU to display output) also increases but the number of detected forged images increases till block size 10 and attains saturation thereafter. Consequently block size should be set to 10 for getting good results in terms of less execution time.en_US
dc.identifier.urihttp://krishikosh.egranth.ac.in/handle/1/5810130581
dc.keywordsImage forgery, Copy move image forgery, Exact match block based method, Block size, Image file formatsen_US
dc.language.isoenen_US
dc.pages54en_US
dc.publisherPunjab Agricultural University, Ludhianaen_US
dc.research.problemAnalysis of image forgery detection algorithmsen_US
dc.subInformation Technologyen_US
dc.subjectnullen_US
dc.themeAnalysis of image forgery detection algorithmsen_US
dc.these.typeM.Tech.en_US
dc.titleAnalysis of image forgery detection algorithmsen_US
dc.typeThesisen_US
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