Image Splicing Forgery Detection Using DCT Coefficients with Multi-Scale LBP

Atif Shah, El Sayed El-Alfy

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

22 Scopus citations

Abstract

Image forensics is an active research area due to the large number of shared images online. These images can be easily manipulated with advanced image editing tools and the changes cannot be captured easily by bare human eyes. In this paper, a novel model is proposed based on features extracted from DCT coefficients and Multi-Scale LBP image transform to blindly detect image splicing, where two or more images are combined into one. The experiments were performed on two publicly available datasets CASIA v.1.0 and v2.0. Using k-fold cross validation, several performance measures were computed and compared with other state-of-The-Art techniques. The proposed technique has demonstrated improved performance with more than 97.3% accuracy and 0.99 area under the ROC curve.

Original languageEnglish
Title of host publication2018 International Conference on Computing Sciences and Engineering, ICCSE 2018 - Proceedings
EditorsHazem Raafat, Mostafa Abd-El-Barr, Muhammad Sarfraz, Paul Manuel
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538646809
DOIs
StatePublished - 5 Jun 2018

Publication series

Name2018 International Conference on Computing Sciences and Engineering, ICCSE 2018 - Proceedings

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Modeling and Simulation

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