A Model for Dynamic Handwritten Signature Verification Based on Neural Network
LI Yua · 2005
Owing to traditional signatures being widely and maturely used in finance or government department hand- written signature verification(HSV),as an effective and efficient kind of biometric based authentication schemes, has a good perspective. But its performace is not good enough because of signatures′easy change. Recently,neural network is coming to used in Pattern Recognition more and more and has archieve good effects. But there are a few of research- es on application of neural network in HSV. This aticale has apposed and implemented a prototype of dynamic HSV based on Back-propagation neural network and has analyzed network structure from experiments. Through 190 own signatures and 371 forged signatures from 10 persons,equal error rate 2.16% are archived.