Image Forgery Detection Using Ensemble of VGG-16 and CNN Architecture
DOI:
https://doi.org/10.5281/zenodo.8210388Keywords:
Deep Learning, Convolutional Neural Networks, Error Level Analysis, Image Processing, Image ForgeryAbstract
Digital image modification or image forgery is easy to do today. The authenticity verification of an image becomes important to protect the image integrity so that the image is not being misused. Error Level Analysis (ELA) can be used to detect the modification in image by lowering the quality of image and comparing the error level. The use of deep learning approach is a state-of-the-art in solving cases of image data classification. This study wants to know the effect of adding ELA extraction process in the image forgery detection using deep learning approach. The Convolutional Neural Network (CNN), which is a deep learning method, is used as a method to do the image forgery detection.References
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Copyright (c) 2023 Smitha B N, G T Mohan Kumar, Manjushree H C, Abhishek M, Nallabothula Sneha
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
CC Attribution-NonCommercial-NoDerivatives 4.0
