MLSingatureAuth

Project Title "Signature verification through handwriting analysis is one of the most common tasks in forensic document analysis. It is very important to compare questioned writing/signatures with the genuine one, when it comes to data protection and identity management. We plan on utilizing machine learning to perform handwriting analysis by matching images of a questioned handwriting with the genuine ones to authenticate writing/signatures under the College of Computing and Informatics. Machine Learning algorithms will adapt and improve their performance as the number of handwriting samples increase for learning and do more accurate analysis. "

Team Members

Dhruv Patel

Dhruv Patel

dhruvap96@gmail.com

Jayden Chen

Jayden Chen

hc523@drexel.edu

Trish Messinger

Trish Messinger

ptm36@drexel.edu

Andrew Vo

Andrew Vo

atv32@drexel.edu

Purav Barot

Purav Barot

pbb34@drexel.edu

"Anthony, Montefiore"

aam375@drexel.edu

Screenshots

Overview

Overview


"MLSigAuth provides an API endpoint, database, and machine learning model services for the client. As shown in Figure 1.1 above, the MLSigAuth System does not include a client. Any client with HTTP POST abilities is able to reach our system and can use functionalities of our system. "

Behind the Scenes

Dr Filippos Vokolos

Senior Design Advisor
Dr Filippos Vokolos

filippos.i.vokolos@drexel.edu

Link 1