Iris Recognition for Personal Identification using LAMSTAR neural network

TL;DR

This paper discusses iris recognition as a biometric method, detailing the process and introducing a LAMSTAR neural network for recognition, demonstrating high accuracy with proper preprocessing.

Contribution

It presents the application of a LAMSTAR neural network for iris recognition, highlighting its effectiveness in distinguishing individuals based on iris features.

Findings

High recognition accuracy achieved with proper preprocessing

LAMSTAR neural network effectively differentiates individuals

Detailed overview of iris recognition process

Abstract

Iris recognition is one of the most important biometric recognition method. This is because the iris texture provides many features such as freckles, coronas, stripes, furrows, crypts, etc. Those features are unique for different people and distinguishable. Such unique features in the anatomical structure of the iris make it possible the differentiation among individuals. So during last years huge number of people have been trying to improve its performance. In this article first different common steps for the Iris recognition system is explained. Then a special type of neural network is used for recognition part. Experimental results show high accuracy can be obtained especially when the primary steps are done well.