A reliable iris recognition algorithm based on reverse biorthogonal wavelet transform

This article describes an iris recognition algorithm designed to analyze noisy iris biometric data. The methods forming part of the authentication process were developed and optimized by the authors using visible wavelength images of an eye taken under unconstrained conditions (at a different perspectives, illuminations, occlusion grades, etc.), mainly contained in the UBIRIS.v2 database. The whole iris authentication system was submitted by the authors to the International Iris Recognition Contest NICE.II, where it took eighth place, while the iris segmentation stage itself took second place in the previous contest — NICE.I.This paper is focused on the iris feature extraction stage — the method developed by the authors to analyze noisy iris biometric data. Several techniques used for more efficient and robust analysis of such images and issues concerning the best wavelet selection are also presented in this paper.

► Performance - eight place within the International Noisy Iris Challenge Evaluation - Part II (NICE.II) contest using the UBIRIS.v2 database.
► A compact signature, which is 324 bits wide.
► Increase of iris image SNR by removing the most noisy blue channel.
► A procedure for distinctive noise-free area selection.