@Article{jnm.2019.06219, AUTHOR = {Weijin Tan, Yunqing Wu, Peng Wu, Beijing Chen,2}, 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} }