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Comparative Analysis of MSER and DTW for Offline Signature Recognition
by
Mohammad Basil,
Bharti Gawali
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 110 - Number 5 |
| Year of Publication: 2015 |
| Authors: Mohammad Basil, Bharti Gawali |
10.5120/19311-0766
|
Mohammad Basil, Bharti Gawali . Comparative Analysis of MSER and DTW for Offline Signature Recognition. International Journal of Computer Applications. 110, 5 ( January 2015), 13-17. DOI=10.5120/19311-0766
@article{
10.5120/19311-0766,
author = {
Mohammad Basil,
Bharti Gawali
},
title = { Comparative Analysis of MSER and DTW for Offline Signature Recognition },
journal = {
International Journal of Computer Applications
},
issue_date = { January 2015 },
volume = { 110 },
number = { 5 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = {
13-17
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume110/number5/19311-0766/
},
doi = { 10.5120/19311-0766 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:32.292847+05:30
%A Mohammad Basil
%A Bharti Gawali
%T Comparative Analysis of MSER and DTW for Offline Signature Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 5
%P 13-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper describes the signature as a one of the most robust and widely used trait in biometric verification. The signature is also known as behavioral biometric property. We present comparative analysis of offline signature recognition based on Dynamic Time Warping (DTW) and Maximally Stable Extremely Regions (MSER). The MSER system reported accuracy of 95. 371% where FAR is 5. 25% and FRR is 4% whereas DTW system reported accuracy of 70. 5% and average horizontal projection WER 70% and average vertical projection WER of 71%.
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Computer Science
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