Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.