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Forgery Detector
- Category
- Mobile app
- Year
- 2024
Stack
- Flutter
- Computer Vision
- ELA
- Firebase
A Flutter thesis app that checks a photo from your phone, decides whether it has been edited, and highlights the tampered regions with an Error Level Analysis overlay, or confirms the image is authentic.
The problem
Edited images spread faster than anyone can fact-check them, and the tampering is often invisible to the eye. This undergraduate thesis app lets anyone check a photo from their phone and see where it was altered.
How it works
The photo is sent to a classifier that runs Error Level Analysis, and the app returns a verdict plus an ELA overlay marking the regions most likely edited, or confirms the image is authentic. Built in Flutter with Firebase auth and storage.
