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: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
IEEE
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69114/1/Online%20signature%20verification%20using%20neural%20network%20and%20Pearson%20correlation%20features.pdf http://psasir.upm.edu.my/id/eprint/69114/ |
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| Summary: | 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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