Authors:
Lina Mi
and
Fumiaki Takeda
Affiliation:
Kochi University of Technology, Japan
Keyword(s):
Writing pressure, RBF, Gaussian function, Neuro-template
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Industrial Applications of Artificial Intelligence
;
Methodologies and Methods
;
Neural Network Software and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
In our previous research work, an individual recognition system with writing pressure employing neuro-template of multiplayer feedforward network with sigmoid function has been developed. Although this system was effective on recognition for known registrant, its rejection capability for counterfeit signature was not good enough for commercial application. In this paper, a new activation function was proposed to improve the rejection performance of the system for counterfeit signature on the premise of ensuring the recognition performance for known signature. The experiment results showed that compared with original system the proposed activation function was seemed to be effective to improve the rejection capability of the system for counterfeit signature with keeping the recognition capability for known signature satisfied.