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Off-line Signature Verification (SV) using the Chi-square statistics

Off-line Signature Verification (SV) using the Chi-square statistics Off-line Signature Verification (SV) is performed using Particle Swarm Optimisation–Neural Network (PSO–NN) algorithm. The technique is based on NN approach trained with PSO algorithm. The presented verification system includes image-processing techniques and other mathematical tools in its structure. To test the performance of the proposed algorithm, three types of forgeries, namely random, unskilled and skilled, are examined. A database with 1350 skilled and genuine signatures taken from 25 volunteers is used for testing the algorithm. The experimental results are presented with comparisons on verification accuracy and statistical figures. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Off-line Signature Verification (SV) using the Chi-square statistics

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2011.037711
Publisher site
See Article on Publisher Site

Abstract

Off-line Signature Verification (SV) is performed using Particle Swarm Optimisation–Neural Network (PSO–NN) algorithm. The technique is based on NN approach trained with PSO algorithm. The presented verification system includes image-processing techniques and other mathematical tools in its structure. To test the performance of the proposed algorithm, three types of forgeries, namely random, unskilled and skilled, are examined. A database with 1350 skilled and genuine signatures taken from 25 volunteers is used for testing the algorithm. The experimental results are presented with comparisons on verification accuracy and statistical figures.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2011

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