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Multimedia Tools and Applications

, Volume 76, Issue 13, pp 14887–14903 | Cite as

A new block-based method for copy move forgery detection under image geometric transforms

  • Junliu Zhong
  • Yanfen Gan
  • Janson Young
  • Lian Huang
  • Peiyu Lin
Article

Abstract

Copy move forgery detection (CMFD) is one of the most active subtopic in forgery scheme. The methods of CMFD are divided into to block-based method and keypoint-based method in general. Compared with keypoint-based method, block-based method can detect undetectable detail without morphology segmentation. But many block-based methods detect the plain copy-move forgeries only. They have been incompetent to detect the post-processing operations such as various geometrical distortions, and then fail to detect the forgery regions accurately. Therefore, this paper presents an improved block-based efficient method for CMFD. Firstly, after pre-processing, an auxiliary overlapped circular block is presented to divide the forged image into overlapped circular blocks. The local and inner image feature is extracted by the Discrete Radial Harmonic Fourier Moments (DRHFMs) with the overlapped circular block from the suspicious image. Then, the similar feature vectors of blocks are searched by 2 Nearest Neighbors (2NN) test. Euclidean distance and correlation coefficient is employed to filter these features and then remove the false matches. Morphologic operation is employed to delete the isolated pixels. A series of experiments are done to analyze the performance for CMFD. Experimental results show that the new DRHFMs can obtain outstanding performance even under image geometrical distortions.

Keywords

Copy move forgery detection Block-based method Discrete radial harmonic Fourier moments Image geometrical distortions 

Notes

Acknowledgements

This work is supported by the 2016 Guangzhou philosophy and social science “Thirteen Five” project-- Digital image forgery cause public opinion incident prevention countermeasures and technical research based on internet information security (No.2016gzqn23).

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Junliu Zhong
    • 1
  • Yanfen Gan
    • 2
  • Janson Young
    • 3
  • Lian Huang
    • 1
  • Peiyu Lin
    • 1
  1. 1.School of Information EngineeringGuangdong Mechanical & Electrical CollegeGuangzhouPeople’s Republic of China
  2. 2.School of Information Science and TechnologyGuangdong University of Foreign Studies South China Business CollegeGuangzhouPeople’s Republic of China
  3. 3.School of ComputersGuangdong University of TechnologyGuangzhouPeople’s Republic of China

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