Recently, digital image forgery detection is an emergent and important area of image processing. Digital image plays a vital role in providing evidence for any unusual incident. However, the image forgery my hide evidence and prevents the detection of such criminal cases due to advancement in image processing and availability of sophisticated software tamper of an image can be easily performed. In this paper, we provide a comprehensive review of the work done on various image forgeries and forensic technology. Many techniques have been proposed to detect image forgery in the literature such as digital watermarking, digital signature, copy-move, image retouching, and splicing. The investigation done in this paper may help the researcher to understand the advantage and handles of the available image forensic technology to develop more efficient algorithms of image forgery detection. Moreover, the comparative study surveys the existing forgery detection mechanisms include deep learning and convolution neural networks concerning it is on benefits and demerits.
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