Online signature verification using neural network and Pearson correlation features

Citation

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).

Abstract

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%.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/ICOS.2013.6735040
Publisher:	IEEE
Keywords:	Online signature verification; Neural network; Pattern recognition; Feature extraction; Pearson correlation coefficients
Depositing User:	Nabilah Mustapa
Date Deposited:	12 Jun 2019 07:35
Last Modified:	12 Jun 2019 07:35
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICOS.2013.6735040
URI:	http://psasir.upm.edu.my/id/eprint/69114
Statistic Details:	View Download Statistic

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