ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES IN SIGNATURE VERIFICATION: AI & ML BASED SIGNATURE PROCESSING SYSTEM
Keywords:
Biometrics, Signature Verification, Artificial Intelligence, Machine Learning, Optical Character Recognition.Abstract
Biometrics systems have been utilized in a variety of applications to help
people authenticate themselves. Signature verification is a typical biometric
method that uses procedures that use various signature requirements.
Because signatures are a widely acknowledged biometric for authentication
and identification of a person, and because each individual has a unique
signature with its own set of behavioral characteristics, it is critical to establish
the signature's legitimacy.
There are a variety of security checking parameters, such as pin codes,
passwords, and finger print scanning, but signature recognition is the most
popular because it is both accurate and cost effective. On the other hand, the
authentication key, such as a pin code or password, is not required to be
remembered.
A significant increase in signature forging instances necessitated the
development of an efficient "Signature Processing System." The Optical
Character Recognition system with Artificial Intelligence and Machine
Learning based technical method for signature verification is presented in this
review paper.
