Fake Image and Document Detection using Machine Learning
Amit Lokre, Sangram Thorat, Pranali Patil, Chetan Gadekar, Yogesh Kisan Mali · Zenodo (CERN European Organization for Nuclear Research) · 2020
In the recent times, the rates of cyber crimes has been increasing tremendously. It has been proven incredibly easy to create fake documents with powerful photo editing softwares. Also social media has proven to be the largest producer of fake images as well. Various malpractices have also been on surge with the help of producing digitally manipulated fake documents. Detection of such fake documents has become mandatory and essential for unveiling of the documents/images based cyber crimes. The tampered images and documents will be detected using neural network .The output of the system will distinguish original document from a digitally morphed document. The system will be implemented using Neural Networks.