The Error Level Analysis method employs the PIL (Python Imaging Library) to examine images for discrepancies in error levels, aiding in the identification of potential image manipulations.
The Noise Analysis technique involves introducing noise, or discrepancies, into an image to reveal areas that may have been tampered with, thus assisting in the detection of potential alterations.
MesoNet is a Convolutional Neural Network (CNN)-based method comprising four Convolutional Blocks. It is designed to detect deepfakes and other image manipulations by analyzing the structural characteristics of the image.
These techniques provide valuable tools for assessing the authenticity of images and identifying potential instances of image manipulation.