Off-line Signature Verification Using an Enhanced Modified Direction Feature with Single and Multi-classifier Approaches

File Size Format
04168418.pdf 2040Kb Adobe PDF View
Title Off-line Signature Verification Using an Enhanced Modified Direction Feature with Single and Multi-classifier Approaches
Author Armand, Stephane; Blumenstein, Michael Myer; Muthukkumarasamy, Vallipuram
Journal Name IEEE Computational Intelligence Magazine
Year Published 2007
Place of publication United States
Publisher IEEE
Abstract The principal objective of this paper was to investigate the efficiency of the enhanced version of the MDF feature extractor for signature verification. Investigations adding new feature values to MDF were performed, assessing the impact on the verification rate of the signatures, using six-fold cross validation. Two different neural classifiers were used and two methodologies for verification were applied. The experiments conducted, whereby MDF was merged with the new features, provided very encouraging results
Peer Reviewed No
Published Yes
Alternative URI http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4168418
Copyright Statement Copyright 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Volume 2
Issue Number 2
Page from 18
Page to 25
ISSN 1556-6048
Date Accessioned 2008-03-27
Date Available 2008-04-24T07:44:47Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Pattern Recognition
URI http://hdl.handle.net/10072/17901
Publication Type Non Refereed Journal Articles
Publication Type Code c2

Brief Record

Griffith University copyright notice