This is an implementation of python script to detect a series of forgeries that can happen in a document. Our basic module supports -signature fraud detection and analysis -copy and move forgery detection -identification document forgery detection -And normal document forgery detection and analysis.
- We have tried impelementing a cloud based web application where user is asked to choose whether he wants to check signature forgery or document forgery.
- Based on his choice he is asked to upload the scanned document. Our machine learning algorithms and neurals network based artificial intelligence detection technique.
- The results generate a graph of the analysis and shows the areas where the forgery has been done. It shows a percentage accuracy of the report which is classified as follows 0% - 10% : Authenic 10% - 55% : Suspicious 55% - 60% : Foreged
-The source code of all the python files used for analysis. -The backend and frontend code of the web application -Several analysis results generated from the code with the disrepencies underlined. -Design of the web-app
- Farid, H., 2009. Seeing is not believing. IEEE Spectrum, 46(8).
- Farid, H., 2009. Image forgery detection. IEEE Signal processing magazine, 26(2), pp.16-25.
- Johnson, M.K. and Farid, H., 2005, August. Exposing digital forgeries by detecting inconsistencies in lighting. In Proceedings of the 7th workshop on Multimedia and security (pp. 1-10). ACM.