Gravitational Search For Designing A Fuzzy Rule-Based Classifiers For Handwritten Signature Verification
Abstract
Handwritten signatures are used in authentication systems as a universal biometric identifier. Signature authenticity verification requires building and training a classifier. This paper describes a new approach to the verification of handwritten signatures by dynamic characteristics with a fuzzy rule-based classifier. It is suggested to use the metaheuristic Gravitational Search Algorithm for the selection of the relevant features and tuning fuzzy rule parameters. The efficiency of the approach was tested with an original dataset; the type II errors in finding the signature authenticity did not exceed 0.5% for the worst model and 0.08% for the best model.
Keywords
Authentication, Verification, Biometrics, Fuzzy Classifier, Gravitational Search Algorithm
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
M. B. Bardamova, A. Konev, I. Hodashinsky and A. Shelupanov, "Gravitational Search For Designing A Fuzzy Rule-Based Classifiers For Handwritten Signature Verification," in Journal of Communications Software and Systems, vol. 15, no. 3, pp. 254-261, August 2019, doi: 10.24138/jcomss.v15i3.678
@article{bardamova2019gravitationalsearch,
author = {Marina Borisovna Bardamova and Anton Konev and Ilya Hodashinsky and Alexander Shelupanov},
title = {Gravitational Search For Designing A Fuzzy Rule-Based Classifiers For Handwritten Signature Verification},
journal = {Journal of Communications Software and Systems},
month = {8},
year = {2019},
volume = {15},
number = {3},
pages = {254--261},
doi = {10.24138/jcomss.v15i3.678},
url = {https://doi.org/10.24138/jcomss.v15i3.678}
}