Open Access
ARTICLE
A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques
School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
*Corresponding Author: Weijin Tan. Email: .
Journal of New Media 2019, 1(1), 11-25. https://doi.org/10.32604/jnm.2019.06219
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.Keywords
Cite This Article
Citations
![cc](https://www.techscience.com/static/images/cc.jpg?t=20230215)