@Article{jnm.2019.06219,
AUTHOR = {Weijin  Tan, Yunqing  Wu, Peng  Wu, Beijing  Chen},
TITLE = {A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques},
JOURNAL = {Journal of New Media},
VOLUME = {1},
YEAR = {2019},
NUMBER = {1},
PAGES = {11--25},
URL = {http://www.techscience.com/JNM/v1n1/28971},
ISSN = {2579-0129},
ABSTRACT = {Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images’ content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions are discussed.},
DOI = {10.32604/jnm.2019.06219}
}