A novel passive forgery detection algorithm for video region duplication

被引:0
作者
Lichao Su
Cuihua Li
机构
[1] Xiamen University,School of Information Science and Engineering
来源
Multidimensional Systems and Signal Processing | 2018年 / 29卷
关键词
Video forgery; Region duplication; Mirror invariant; Passive forensics;
D O I
暂无
中图分类号
学科分类号
摘要
Forgery involving region duplication is one of the most common types of video tampering. However, few algorithms have been suggested for detecting this type of forgery effectively, especially for videos to which a mirroring operation was applied. In this paper, we summarize the properties of duplication forgery of video regions and propose a novel algorithm to detect this forgery. First, the algorithm extracts the feature points in the current frame. The tampered areas in the current frame are then searched, which is implemented in three steps. Finally, our algorithm detects the tampered areas in the remaining frames using spatio-temporal context learning and outputs the detection results. The experimental results demonstrate the satisfactory performance of our algorithm for detecting videos subjected to mirror operations and its higher efficiency than previous algorithms.
引用
收藏
页码:1173 / 1190
页数:17
相关论文
共 35 条
  • [1] Al-Qershi OM(2013)Passive detection of copy-move forgery in digital images: State-of-the-art Forensic Science International 231 284-295
  • [2] Khoo BE(2011)A SIFT-based forensic method for copy-move attack detection and transformation recovery IEEE Transactions on Information Forensics and Security 6 1099-1110
  • [3] Amerini I(2012)A robust detection algorithm for copy-move forgery in digital images Forensic Science International 214 33-43
  • [4] Ballan L(2012)Exposing postprocessed copy-paste forgeries through transform-invariant features IEEE Transactions on Information Forensics and Security 7 1018-1028
  • [5] Caldelli R(2009)Passive detection of doctored JPEG image via block artifact grid extraction Signal Processing 89 1821-1829
  • [6] Del Bimbo A(2004)Distinctive image features from scale-invariant keypoints International Journal of Computer Vision 60 91-110
  • [7] Serra G(2012)An overview on video forensics APSIPA Transactions on Signal and Information Processing 1 e2-1716
  • [8] Cao Y(2015)Image forgery detection using adaptive oversegmentation and feature point matching IEEE Transactions on Information Forensics and Security 10 1705-348
  • [9] Gao T(2008)Overview of state-of-the-art in digital image forensics Algorithms, Architectures and Information Systems Security 3 325-191
  • [10] Fan L(2003)Contextual priming for object detection International Journal of Computer Vision 53 169-186