文章基本信息

标题：Copy Move Forgery Detection Techniques: A Comprehensive Survey of Challenges and Future Directions
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作者：Ibrahim A. Zedan ; Mona M. Soliman ; Khaled M. Elsayed 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：7
DOI：10.14569/IJACSA.2021.0120729
语种：English
出版社：Science and Information Society (SAI)
摘要：Digital Image Forensics is a growing field of image processing that attempts to gain objective ‎proof ‎of the origin and veracity of a visual image. Copy-move forgery detection (CMFD) has ‎currently ‎become an active research topic in the passive/blind image forensics field. There has no ‎doubt that ‎conventional techniques and especially the keypoint based techniques have pushed the ‎CMFD ‎forward in the previous two decades. However, CMFD techniques in general and ‎conventional ‎techniques in particular suffer from several challenges. And thus, increasing approaches ‎are exploiting ‎deep learning for CMFD. In this survey, we cover the conventional and the ‎deep learning ‎based CMFD techniques from a new perspective. We classify the ‎CMFD techniques into several ‎classifications according to the detection methodology, the detection paradigm, and the detection ‎capability‎. We discuss the ‎challenges facing the CMFD techniques as well as the ways for solving ‎them. In addition, this survey covers the evaluation metrics‎ and datasets commonly utilized for ‎CMFD. Also, we are ‎debating and proposing certain plans for future research. This survey will be ‎helpful for the researchers’ ‎as it master the recent trends of CMFD and outline some future research ‎directions.
关键词：Image forensics; copy-move forgery detection (CMFD);conventional techniques; deep learning techniques