Copy-move Image Forgery Localization Using Deep Feature Pyramidal Network

M. Sabeena, Lizy Abraham, P. R. Sreelekshmi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fake news, frequently making use of tampered photos, has currently emerged as a global epidemic, mainly due to the widespread use of social media as a present alternative to traditional news outlets. This development is often due to the swiftly declining price of advanced cameras and phones, which prompts the simple making of computerized pictures. The accessibility and usability of picture-altering softwares make picture-altering or controlling processes significantly simple, regardless of whether it is for the blameless or malicious plan. Various investigations have been utilized around to distinguish this sort of controlled media to deal with this issue. This paper proposes an efficient technique of copy-move forgery detection using the deep learning method. Two deep learning models such as Buster Net and VGG with FPN are used here to detect copy move forgery in digital images. The two models' performance is evaluated using the CoMoFoD dataset. The experimental result shows that VGG with FPN outperforms the Buster Net model for detecting forgery in images with an accuracy of 99.8% whereas the accuracy for the Buster Net model is 96.9%.

Original languageEnglish
Title of host publication10th International Conference on Advances in Computing and Communications, ICACC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665439190
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event10th International Conference on Advances in Computing and Communications, ICACC 2021 - Kochi, India
Duration: 21 Oct 202123 Oct 2021

Publication series

Name10th International Conference on Advances in Computing and Communications, ICACC 2021

Conference

Conference10th International Conference on Advances in Computing and Communications, ICACC 2021
Country/TerritoryIndia
CityKochi
Period21/10/202123/10/2021

Keywords

  • Buster Net
  • Copy move forgery
  • Deep learning models
  • Performance analysis
  • VGG with FPN

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