Abstract
Images are a staple in the world of digital media, the manipulation of digital images can pose a serious threat due to propagation of misinformation. With the increasing pace of technological innovation in digital image forensics, the quality of generated forged images has reached a point where forgeries are becoming imperceptible. Images can come from various sources and can take many forms, thus passive (blind) techniques of image forgery detection are preferred since these do not require any prior information about an image. The most common kind of passive image forgery detection include copy-move and image splicing forgery detection. An attempt is made to discuss recent research in both fields and to provide a glimpse into how state-of-the-art techniques employ the use of various processing algorithms to achieve adequate results. A detailed explanation of classification of image forgery detection techniques has been done along with a brief background on detection techniques, followed by a table summarizing the discussion. An assessment of the popular datasets used in image forgery detection is also mentioned.
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