Open AccessA Comprehensive Study on Offline Signature Verification
Author(s) -
Neha Sharma,
Sheifali Gupta,
Puneet Mehta
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1969/1/012044
Subject(s) - computer science , signature (topology) , biometrics , task (project management) , process (computing) , documentation , field (mathematics) , artificial intelligence , machine learning , computer security , engineering , programming language , systems engineering , geometry , mathematics , pure mathematics
Handwritten Signatures are special types of behavioural biometric which are used in many applications such as banks, credit cards, passport, check processing, and financial documentation, etc. Verification of these signatures is a challenging task especially in the case of offline where there is no information of signing process. So there is a need for a system that can distinguish between the genuine and the forged signature to avoid the chances of theft or fraud. Many types of researches have been done in this area in the last three decades. Earlier this task was performed by handcrafted features and recently deep learning techniques have been employed for this task, but still, there is a chance of enhancement in the accuracy of the system. In this paper, we present a comprehensive study of the work done in the field of offline signature verification and also the challenges which are still present in this area.