Date of Publication :10th November 2020

Abstract: Image processing is one of the most demanding research areas now a day because various fields like medical, engineering, research, industry, e-commerce business etc. mainly based on digital images. It attracts researcher’s focus because any tampering on authenticated digital images may changes the whole result. It faces misuse of original documents by unauthorized users. From the beginning of research in image processing field researchers tried to develop effective algorithms that prevent the digital images from any tampering attacks. There are many types of tampering like copy-move, image splicing and image resampling perform on digital images. The tampering operation (TO) on digital images mainly divided into two types: The first one is Active Tampering operation and second one is Passive tampering operation. In this paper we try to focus on various copy-move forgery detection (CMFD) methods that come in passive image tampering like PCA, SIFT, SURF etc. It may be block based and key point-based methods. The acceptance of developed algorithm increased widely if it performs effectively on benchmark datasets. We also cover some of demanding datasets for copy-move tampering operation like MICC F-220, CoMoFoD etc.

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