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Multilevel fusion for fast online signature recognition using multi-section VQ and time modelling

journal contribution
posted on 2015-07-01, 00:00 authored by Imran RazzakImran Razzak, B Alhaqbani
© 2014, The Natural Computing Applications Forum. Signature recognition is one of the most important biometrics authentication methods, is an integral part of current business activities, and is considered a non-invasive and non-threatening process. This paper presents an online signature verification system using multi-section VQ. We have used multi-section codebooks for signature recognition by splitting the signature into several sections with every section having its own codebook. The final result is based on the score level fusion of the results of each codebook. Moreover, multilevel fusion is performed in this trial to improve the accuracy. We have used SVC database that contains skilled forgery samples. Our experimental results on SVC database have shown 100 % accuracy with 0.003 EER.

History

Journal

Neural computing and applications

Volume

26

Pagination

1117-1127

Location

Cham, Switzerland

ISSN

0941-0643

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

5

Publisher

Springer

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