DETECTION AND MATCHING OF IRIS REGION IN IMAGES TAKEN IN UNFAVORABLE CONDITIONS LIKE LIGHT CAMERA DISTANCE ETC. FOR MAKING IRIS RECOGNITION SYSTEMS MORE EFFECTIVE

Abstract

Iris recognition has become a hot research topic driven by its wide applications in national ID card, border
control, banking, etc. Iris is a ring-shaped region of human eye with rich texture information under near infrared
illumination. Iris texture is regarded as a genotypic biometric pattern and stable during life so that iris recognition provides
an extremely reliable method for individual authentication. Iris recognition aims to assign unique identity label to each iris
image based on automatic preprocessing, feature analysis and feature matching. State-of-the-art iris recognition methods
include Gabor phase demodulation, ordinal measures, etc. Iris recognition systems have made tremendous inroads over the
past decade, but work remains to improve their accuracy in environments characterized by unfavorable lighting, large stand -
off distances, and moving subjects. We have proposed a method for iris extraction and matching in these unfavorable
conditions. The results show that it gives better performance in valid iris detection by removing upper and lower eyelids
accurately.