Future Biometric Passports and Neural Networks

Authors

  • Omar Al Zoubi

  • Dr. Kheder Durah

  • Bilal Alzoubi

Keywords:

prints, retina, iris, DNA

Abstract

Due to the increase in the number of crimes and different ways they are perpetrated, demand has increased on the means that increase the level of security accuracy in the places that need special kind of protection, and places that require verifying the identity of those who demand access, such as computer networks, banks and home land security departments. There are many ways to identify people and grant them the required access; these methods include: What people have? (like an access card or key) and What people know? (like password); Moreover, there are physical biometric features such as (figure prints, retina, iris, DNA,etc) and behavioral biometric features such as (signature, voice, walking, etc). Recently, experience proved that using the iris is the best and more accurate than any other way and it will be the target of our research. There are several ways to increase the level of security that have been innovated, most important of which was using the biometrics. The most accurate biometric feature is the human eye iris, due to the characteristics it enjoys, and which make it possible to be used to identify people. The eye iris texture differs from one person to another; it even differs between identical twins, and the right and left eyes of the same person too. The aim of this research is to design an algorithm to recognize the iris for using it to identify people and create an international biometric passport for that person.

How to Cite

Omar Al Zoubi, Dr. Kheder Durah, & Bilal Alzoubi. (2011). Future Biometric Passports and Neural Networks. Global Journal of Computer Science and Technology, 11(7), 21–26. Retrieved from https://computerresearch.org/index.php/computer/article/view/723

Future Biometric Passports and Neural Networks

Published

2011-03-15