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Reseach Article

Online Signature Verification in Banking Application: Biometrics SaaS Implementation

Published on July 2016 by Joel Philip, Vinayak A. Bharadi
International Conference on Communication Computing and Virtualization
Foundation of Computer Science USA
ICCCV2016 - Number 1
July 2016
Authors: Joel Philip, Vinayak A. Bharadi
ae608315-c145-4cc1-b023-db99ac117f26

Joel Philip, Vinayak A. Bharadi . Online Signature Verification in Banking Application: Biometrics SaaS Implementation. International Conference on Communication Computing and Virtualization. ICCCV2016, 1 (July 2016), 0-0.

@article{
author = { Joel Philip, Vinayak A. Bharadi },
title = { Online Signature Verification in Banking Application: Biometrics SaaS Implementation },
journal = { International Conference on Communication Computing and Virtualization },
issue_date = { July 2016 },
volume = { ICCCV2016 },
number = { 1 },
month = { July },
year = { 2016 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/icccv2016/number1/916-1658/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Communication Computing and Virtualization
%A Joel Philip
%A Vinayak A. Bharadi
%T Online Signature Verification in Banking Application: Biometrics SaaS Implementation
%J International Conference on Communication Computing and Virtualization
%@ 2249-0868
%V ICCCV2016
%N 1
%P 0-0
%D 2016
%I International Journal of Applied Information Systems
Abstract

Signature recognition and identification is a vital behavioral biometric trait. Signature recognition system can be used to identify precisely user identity by making use of signature information such as x, y variations and pressure from a tablet PC. This makes way for using dynamic, i. e. , online handwritten signature based biometric system is more accurate than the static ones, hence can be useful for banking applications. In this paper new set of features are proposed for online or dynamic signature recognition. In this research, feature vector and their extraction mechanism is implemented using Webber Local Descriptor (WLD). Thus, helping many banking applications to identify forgery of signatures. The performance of proposed feature vector is further improved by provision of soft biometric traits of the signature.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Banking Applications Webber Local Descriptors Texture Features Online Signature