Signature Forgery and Veracity Detection using Machine Learning

Abstract

This research paper addresses the escalating risk of fraud signatures in banking transactions. It introduces a Signature Forgery Detection System that utilizes offline verification and diverse geometric measures to discern genuine from forged signatures. With the prevalence of signature-based identity verification in financial transactions and the absence of foolproof systems, the proposed system aims to enhance the security of banking by efficiently detecting and preventing signature forgery.