Copy-Move Forgery Detection Based on Local Gabor Wavelets Patterns

  • Chao-Lung ChouEmail author
  • Jen-Chun Lee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 733)


Nowadays digital images are more and more easily to be modified or tampered intentionally by most people due to the rapid development of powerful image processing software. Various methods of digital image forgery exist, such as image splicing, copy-move forgery, and image retouching. Copy-move is one of the typical image forgery methods, in which a part of an image is duplicated and used to replace another part of the same image at a different location. In this paper, we proposed a block-based passive detect copy-move forgery detection method based on local Gabor wavelets patterns (LGWP) with the advantages of high performance texture analysis of Gabor filter and rotation-invariant ability of uniform local binary pattern (LBP). Experiment results demonstrate the ability of the proposed method to detect copy-move forgery and precisely locate the duplicated regions, even when the forgery images are distorted by JPEG compression, blurring, brightness adjustment and rotation.


Copy-move forgery Image forgery detection Local Gabor wavelets patterns (LGWP) 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and Information Engineering, Chung Cheng Institute of TechnologyNational Defense UniversityTaoyuanTaiwan
  2. 2.Department of Electrical EngineeringChinese Naval AcademyKaohsiungTaiwan

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