Signature verification using self-organizing feature map

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F03%3A00000237" target="_blank" >RIV/49777513:23520/03:00000237 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Signature verification using self-organizing feature map

Original language description

In this paper we describe the use of the SOFM neural network model for signature verification. The biometric data of all signatures were acquired by a special digital data acquisition pen and fast wavelet transformation was used for feature extraction. The part of authentic signature data was used for training the SOFM signature verifer. The architecture of the verifer and achieved results are discussed here and ideas for future research are also suggested.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2003

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CIRAS 2003

ISBN

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ISSN

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e-ISSN

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Number of pages

4

Pages from-to

1-4

Publisher name

National University of Singapore

Place of publication

Singapore

Event location

Singapore

Event date

Dec 15, 2003

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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