Novel Optimization Based Hybrid Self-Organizing Map Classifiers for Iris Image Recognition

Authors

J. Jenkin Winston¹, Gul Fatma Turker², Utku Kose^2, , D. Jude Hemanth^{1, *}

¹Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India

²Department of Computer Science Engineering, Suleyman Demirel University, Isparta, Turkey

^*Corresponding author. Email: judehemanth@karunya.edu

DOI

10.2991/ijcis.d.200721.001How to use a DOI?

Keywords

Biometrics; Artificial neural network; Hybrid classifier; Optimization; Iris

Abstract

The concern over security in all fields has intensified over the years. The prefatory phase of providing security begins with authentication to provide access. In many scenarios, this authentication is provided by biometric systems. Moreover, the threat of pandemic has made the people to think of hygienic systems which are noninvasive. Iris image recognition is one such noninvasive biometric system that can provide automated authentication. Self-organizing map is an artificial neural network which helps in iris image recognition. This network has the ability to learn the input features and perform classification. However, from the literature it is observed that the performance of this classifier has scope for refinement to yield better classification. In this paper, heterogeneous methods are adapted to improve the performance of the classifier for iris image recognition. The heterogeneous methods involve the application of Gravity Search Optimization, Teacher Learning Based Optimization, Whale Optimization and Gray Wolf Optimization in the training process of the self-organizing map classifier. This method was tested on iris images from IIT-Delhi database. The results of the experiment show that the proposed method performs better.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - J. Jenkin Winston
AU  - Gul Fatma Turker
AU  - Utku Kose
AU  - D. Jude Hemanth
PY  - 2020
DA  - 2020/08/06
TI  - Novel Optimization Based Hybrid Self-Organizing Map Classifiers for Iris Image Recognition
JO  - International Journal of Computational Intelligence Systems
SP  - 1048
EP  - 1058
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200721.001
DO  - 10.2991/ijcis.d.200721.001
ID  - Winston2020
ER  -