State ofthe art of copy-move forgery detection techniques: a review

The different methods for processing and detecting forgery in digital images have received growing attention recently. This is due to the availability of up-to-date editing software and sophisticated digital cameras, which simplify the duplication of regions for the forgers where part of an image is pasted to another location to conceal undesirable objects. An example of these methods is copy-move (i.e., Cloning) forgery in digital images. Detection of copy-move forgery to search the copied regions and they're pasted ones, but detection may vary based on whether there has been any post-processing on the copied part before paste it to another party. Generally, forgers apply some operations such as filtering, resizing, rotation, JPEG compression, and noise addition to the original image before pasting, which make it difficult to detect copy-move forgery. Hence, forgery detector should be robust to all manipulations and up-to-date editing software. In the literature, researchers described the working process of copy-move forgery based on the similarity and based on the relationship between the original image parts and pasted one within the same image. This paper highlights current issues in the forgery detection approaches and all their comparative analysis.

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