Iris recognition using Ridgelet transform

Abstract

Iris Recognition is a reliable biometric identification system that uses fine textures of the Iris for person identification and verification. This paper presents a novel algorithm for accurate iris recognition using Ridgelet transform. In this work, the pupil and limbic boundaries are detected by using the equation of circle. Canny edge detection scheme is used for iris boundary detection. After that, eyelids are localized via edge detection followed by curve fitting. A rank filter is adopted for eyelash removal and a histogram filter, for tackling the shape irregularity of eyelids. Finally edge fitting is performed to deal with non circular iris boundaries. After edge fitting, Ridgelet transform is applied and Co-occurrence matrix is computed for each sub band for feature extraction. Here, the benchmark database CASIA-IRIS-V3 (Interval) is used for identification and recognition.