Online signature verification using neural network and Pearson correlation features

In this paper, we proposed a method for feature extraction in online signature verification. We first used signature coordinate points and pen pressure of all signatures, which are available in the SIGMA database. Then, Pearson correlation coefficients were selected for feature extraction. The obtai...

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Main Authors: Iranmanesh, Vahab, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Wan Adnan, Wan Azizun, Malallah, Fahad Layth, Yussof, Salman
Format: Conference or Workshop Item
Language:English
Published: IEEE 2013
Online Access:http://psasir.upm.edu.my/id/eprint/69114/
http://psasir.upm.edu.my/id/eprint/69114/1/Online%20signature%20verification%20using%20neural%20network%20and%20Pearson%20correlation%20features.pdf
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author Iranmanesh, Vahab
Syed Ahmad Abdul Rahman, Sharifah Mumtazah
Wan Adnan, Wan Azizun
Malallah, Fahad Layth
Yussof, Salman
author_facet Iranmanesh, Vahab
Syed Ahmad Abdul Rahman, Sharifah Mumtazah
Wan Adnan, Wan Azizun
Malallah, Fahad Layth
Yussof, Salman
author_sort Iranmanesh, Vahab
building UPM Institutional Repository
collection Online Access
description In this paper, we proposed a method for feature extraction in online signature verification. We first used signature coordinate points and pen pressure of all signatures, which are available in the SIGMA database. Then, Pearson correlation coefficients were selected for feature extraction. The obtained features were used in back-propagation neural network for verification. The results indicate an accuracy of 82.42%.
first_indexed 2025-11-15T11:39:43Z
format Conference or Workshop Item
id upm-69114
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T11:39:43Z
publishDate 2013
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling upm-691142019-06-12T07:35:02Z http://psasir.upm.edu.my/id/eprint/69114/ Online signature verification using neural network and Pearson correlation features Iranmanesh, Vahab Syed Ahmad Abdul Rahman, Sharifah Mumtazah Wan Adnan, Wan Azizun Malallah, Fahad Layth Yussof, Salman In this paper, we proposed a method for feature extraction in online signature verification. We first used signature coordinate points and pen pressure of all signatures, which are available in the SIGMA database. Then, Pearson correlation coefficients were selected for feature extraction. The obtained features were used in back-propagation neural network for verification. The results indicate an accuracy of 82.42%. IEEE 2013 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69114/1/Online%20signature%20verification%20using%20neural%20network%20and%20Pearson%20correlation%20features.pdf Iranmanesh, Vahab and Syed Ahmad Abdul Rahman, Sharifah Mumtazah and Wan Adnan, Wan Azizun and Malallah, Fahad Layth and Yussof, Salman (2013) Online signature verification using neural network and Pearson correlation features. In: 2013 IEEE Conference on Open Systems (ICOS), 2-4 Dec. 2013, Sarawak, Malaysia. (pp. 18-21). 10.1109/ICOS.2013.6735040
spellingShingle Iranmanesh, Vahab
Syed Ahmad Abdul Rahman, Sharifah Mumtazah
Wan Adnan, Wan Azizun
Malallah, Fahad Layth
Yussof, Salman
Online signature verification using neural network and Pearson correlation features
title Online signature verification using neural network and Pearson correlation features
title_full Online signature verification using neural network and Pearson correlation features
title_fullStr Online signature verification using neural network and Pearson correlation features
title_full_unstemmed Online signature verification using neural network and Pearson correlation features
title_short Online signature verification using neural network and Pearson correlation features
title_sort online signature verification using neural network and pearson correlation features
url http://psasir.upm.edu.my/id/eprint/69114/
http://psasir.upm.edu.my/id/eprint/69114/
http://psasir.upm.edu.my/id/eprint/69114/1/Online%20signature%20verification%20using%20neural%20network%20and%20Pearson%20correlation%20features.pdf