  A new approach in iris recognition based on Circular Fuzzy Iris Segmentation
(CFIS) and Gabor Analytic Iris Texture Binary Encoder (GAITBE) is proposed and
tested here. CFIS procedure is designed to guarantee that similar iris segments
will be obtained for similar eye images, despite the fact that the degree of
occlusion may vary from one image to another. Its result is a circular iris
ring (concentric with the pupil) which approximates the actual iris. GAITBE
proves better encoding of statistical independence between the iris codes
extracted from different irides using Hilbert Transform. Irides from University
of Bath Iris Database are binary encoded on two different lengths (768 / 192
bytes) and tested in both single-enrollment and multi-enrollment identification
scenarios. All cases illustrate the capacity of the newly proposed methodology
to narrow down the distribution of inter-class matching scores, and
consequently, to guarantee a steeper descent of the False Accept Rate.
