Application of Individual Authentication System

Abstract

In this research, we discuss signature of individual authentication. While, the individual authentication with signature is comfort and effective for ordinary authentication system.
Especially, discuss pen pressure. From previous research, the experimental results with various data from several persons show excellent.
However, in practical use, there is some miss-recognition for counterfeit writing, which another person imitatesone's signature.
So, we apply neural network with radial bases function(RBF).
In this paper, RBF is proposed to improve rejection capabilities of the system on the premise of ensuring the effectively on known patterns recognition.