Iris Recognition for Personal Identification using LAMSTAR neural network
This is an incremental improvement in biometric identification for security applications.
The paper tackles iris recognition for personal identification by using a LAMSTAR neural network for the recognition step, achieving high accuracy when preprocessing steps are properly executed.
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.