Automatic iris recognition using neural networks and wavelet
Mohamed Elgendi, Mohamed Eladawy, Hisham Keshk · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
It's known that any iris recognition system is composed of four steps: iris image acquisition, iris texture isolation, features extraction, and classification. In the acquisition phase, our system begins with identifying the human iris automatically in a given image using neural networks to test whether it contains iris or not. If the iris exists in the acquired image it goes to the second step which is the iris texture isolation to localize the pupil boundaries, localize the iris boundaries, extract the iris texture, convert the iris texture to the polar coordinate system and then equalize the histogram of the rectangular iris texture. In the features extraction phase, our system uses the Haar wavelet to extract 72 features. In the classification phase, our system uses the matching ratio to identify or reject the subject.