Open Access Open Access  Restricted Access Subscription Access

IRIS Recognition for Personal Identification Using Lamstar Neural Network


Affiliations
1 Department of Electrical and Computer Engineering, University of California, Santa Cruz City, United States
 

One of the promising biometric recognition method is Iris recognition. 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 year's 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.

Keywords

Iris Recognition, Biometric Identification, Pattern Recognition, Automatic Segmentation.
User
Notifications
Font Size

Abstract Views: 362

PDF Views: 166




  • IRIS Recognition for Personal Identification Using Lamstar Neural Network

Abstract Views: 362  |  PDF Views: 166

Authors

Shideh Homayon
Department of Electrical and Computer Engineering, University of California, Santa Cruz City, United States

Abstract


One of the promising biometric recognition method is Iris recognition. 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 year's 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.

Keywords


Iris Recognition, Biometric Identification, Pattern Recognition, Automatic Segmentation.