IRIS recognition using conventional approach

The proper functioning of many of our social, financial, and political structures nowadays relies on the correct identification of people. Reliable and unique identification of people is a difficult problem; people typically use identification cards, usernames, or passwords to prove their identities, however passwords can be forgotten, and identification cards can be lost or stolen. Biometric methods, which identify people based on physical or behavioural characteristics, are of interest because people cannot forget or lose their physical characteristics in the way that they can lose passwords or identity cards. Biometric systems have been developed based on fingerprints, facial features, voice, hand geometry, handwriting, the retina, and the one presented in this work, the iris. Iris is difficult issue because of pre-processing and segmentation phases. In other word, preparing the iris in a rectangular image format is a complicated issue. This work concentrates on segmentation issue. A good segmentation reflects on perfect recognition with minimum number of features. With only three features, 100% recognition can be achieved. A comparative study between different methodologies is introduced. This study shows the efficiency of the proposed model.