Iris Detection and Normalization in Image Domain Based on Morphological Features

The interface of computer technologies and biology is having a huge impact on society. Human recognition research projects promises new life to many security-consulting. Iris recognition is considered to be the most reliable biometric authentication system. Very few iris recognition algorithms were commercialized. We implemented a system that process two different kinds of iris databases: CASIA and UPOL. The first is grayscale data; noise free of reflections but containing obstructions; e.g. eyelids and eyelashes. While the second is RGB data; noise free of obstructions; because it is segmented, but it contains reflections. The circular iris and pupil of the eye image were segmented using Morphological operators and Hough transform. The localized iris region was then normalized into a rectangular block to account for imaging inconsistencies. This method provides accurate features as well as accurate signature of the human iris in a simple and fast way.