auto-encoder-based forgery detection tool for mammogram images
-
Updated
Jun 18, 2022 - Python
auto-encoder-based forgery detection tool for mammogram images
Multi-feature Forgery Detection Deep-Learning based Framework
Bag of visual words AI model made with Scikit-learn and OpenCV
A Rust implementation of ZERO: a JPEG grid detector applied to forgery detection in digital images.
Bachelor's Thesis - application for detecting digital image forgeries. Praca Inzynierska - aplikacja do wykrywania falszerstw w obrazach cyfrowych
An algorithm that is completely robust to Intensity/ Brightness varied copy move forgery is proposed in this algorithm.
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Employing Error Level Analysis (ELA) and Edge Detection techniques, this project aims to identify potential image forgery by analyzing discrepancies in error levels and abrupt intensity changes within images.
Forgegy Image Detection Using Error level Analysis and Deep Learning
Iterative Copy-Move Forgery Detection based on a new Interest Point Detector
[ICAPR 2017] Image Hash Minimization for Tamper Detection
Implementation of the famous Camera Noise Fingerprint "NoisePrint" in Pytorch
TensorFlow/Keras examples and notes.
The assignments and projects on Digital Image Processing
IMDetector is a Python module for image manipulation detection.
Authenticating Bob Ross Paintings using Convolutional Neural Networks
Copy-Move forgery database with similar but Genuine objects. ICIP2016 paper
AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection (NeurIPS 2020)
🖼️ 🕵️ Forgery Detection on Images
IFAKE is an application for detecting image and video forgery, designed to help users verify the authenticity of digital media. This repository also contains the AI model and dataset that we developed for image tampering detection, providing an effective solution for detecting image and video manipulations.
Add a description, image, and links to the forgery-detection topic page so that developers can more easily learn about it.
To associate your repository with the forgery-detection topic, visit your repo's landing page and select "manage topics."