The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES
Transactions ID Number: 20-831
Full Name: Matteo Nunziati
Position: Researcher
Age: ON
Sex: Male
Address: via santa marta 3, florence , Italy
Country: ITALY
Tel:
Tel prefix:
Fax:
E-mail address: matteo.nunziati@unifi.it
Other E-mails:
Title of the Paper: Offline continuous adaptation of templates for signature identification
Authors as they appear in the Paper: Monica Carfagni, Lapo Governi, Matteo Nunziati
Email addresses of all the authors: monica.carfagni@unifi.it, lapo.governi@unifi.it, matteo.nunziati@unifi.it
Number of paper pages: 8
Abstract: Automatic on-line signature identification is a procedure which allows a machine to identify a subject among a cohort of individuals by using only the subject's signature. The following paper deals with features and models required in order to allow a machine to learn and discriminate people on the basis of such a biometric trait. The proposed solution presents a neural network based framework for template adaptation which has demonstrated to improve the resilience of a system, when it has to face with forgeries, that is, fake signatures which are used in order to attack the system and grant unauthorized access to services. The proposed framework provides an improved security level of 35% with respect to non adapted systems.
Keywords: adaptation, artificial neural networks, identification, signature
EXTENSION of the file: .pdf
Special (Invited) Session: An improved model and feature set for signature recognition
Organizer of the Session: 510-158
How Did you learn about congress:
IP ADDRESS: 150.217.48.104
