Research Article
Frequency based Digital Image Forgery Detection Through Optimal Threshold Using SOELTP
@ARTICLE{10.4108/eai.2-12-2021.172360, author={Vikas Srivastava and Sanjay Kumar Yadav}, title={ Frequency based Digital Image Forgery Detection Through Optimal Threshold Using SOELTP}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={9}, number={4}, publisher={EAI}, journal_a={SIS}, year={2022}, month={8}, keywords={YCbCr, DWT, SOELTP, ELTP, Accuracy}, doi={10.4108/eai.2-12-2021.172360} }- Vikas Srivastava
Sanjay Kumar Yadav
Year: 2022
Frequency based Digital Image Forgery Detection Through Optimal Threshold Using SOELTP
SIS
EAI
DOI: 10.4108/eai.2-12-2021.172360
Abstract
INTRODUCTION: Image forgery detection is a very challenging task now a day. Latest tools and applications make it easy. Artefact change our thought and perceptions. OBJECTIVES: A forgery detection system is a need of time to detect image forgery. METHODS: We proposed a blind image forgery detection technique. Optimal threshold-based Enhanced Local Ternary Pattern (OELTP) technique implemented on smoothed image. Features are extracted in the form of frequency to implement Discrete Wavelet Transform (DWT) on the chrominance component of the image. Support Vector Machine is used for classification. RESULTS: The accuracy of the forgery detection on the proposed technique is better than some of the previous states of work. CONCLUSION: Image forgery detection system performance has been improved by better localization of the forgery. Performance of the global threshold improved by using the latest technique, and reducing the operational complexity.
Copyright © 2021 Vikas Srivastava et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.