Abstract
The credence of digital images in terms of their authenticity and integrity especially in medical records, scientific publications, celebrity magazines, news items, political campaigns or when presented as a proof in a courtroom is being questioned as easy to use and cost-effective image editing tools with malicious intend can be used to make copy-move forgery to these images. Consequently, efficient, fast, robust, and computer vision-based image forgery detection technique have become essential to ensure digital image authenticity and integrity. The current work surveys recent progress of copy-move forgery detection technologies to identify factors that impede forgery detection and reviews accuracy of different proposed methods. The work presents a broader classification of different image forgery detection techniques along with their pros and cons. Further, a comprehensive study of block-based copy-move forgery detection methods has been made and discussed with respect to performance evaluation parameters including feature vector length, block size, precision, recall, and F1 score.
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