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Reseach Article

Security Evaluation of Online Signature Verification System using Webcams

by T. Venkatesh, Balaji.s, Chakravarthy A S N
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 15
Year of Publication: 2012
Authors: T. Venkatesh, Balaji.s, Chakravarthy A S N
10.5120/5617-7901

T. Venkatesh, Balaji.s, Chakravarthy A S N . Security Evaluation of Online Signature Verification System using Webcams. International Journal of Computer Applications. 41, 15 ( March 2012), 28-33. DOI=10.5120/5617-7901

@article{ 10.5120/5617-7901,
author = { T. Venkatesh, Balaji.s, Chakravarthy A S N },
title = { Security Evaluation of Online Signature Verification System using Webcams },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 15 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number15/5617-7901/ },
doi = { 10.5120/5617-7901 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:30:18.101777+05:30
%A T. Venkatesh
%A Balaji.s
%A Chakravarthy A S N
%T Security Evaluation of Online Signature Verification System using Webcams
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 15
%P 28-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper mainly focused on the evaluation of an authentication system based on personal signatures. Signature verification is an important research topic in the area of biometric authentication. In this paper the work is done in such a way that the signatures are captured using WEBCAM. A visual-based online signature verification system in which the signer's pen tip is tracked. The data acquisition of the system consists of only low-cost cameras (webcams) and does not need special equipment such as an electronic tablet. Online signature data is obtained from the images captured by the webcams by tracking the pen tip. The pen tip tracking is implemented by the Sequential Monte Carlo method in real time. Then the distance between the input signature data and reference signature data enrolled in advance is computed using Dynamic Time Warping (DTW). Finally, the input signature is classified as genuine or a forgery by comparing the distance with a threshold.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Biometric Signature Identification Security Verification