DocumentCode :
820870
Title :
Off-line Signature Verification Using an Enhanced Modified Direction Feature with Single and Multi-classifier Approaches
Author :
Armand, Stéphane ; Blumenstein, Michael ; Muthukkumarasamy, Vallipuram
Volume :
2
Issue :
2
fYear :
2007
fDate :
5/1/2007 12:00:00 AM
Firstpage :
18
Lastpage :
25
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
Keywords :
feature extraction; handwriting recognition; image classification; neural nets; MDF feature extractor; modified direction feature; neural classifiers; offline signature verification;
fLanguage :
English
Journal_Title :
Computational Intelligence Magazine, IEEE
Publisher :
ieee
ISSN :
1556-603X
Type :
jour
DOI :
10.1109/MCI.2007.353417
Filename :
4168418
Link To Document :
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