Fusion of Thresholding and Limbic Pupilliary Boundary Algorithms for Iris Segmentation Process

Abstract

Iris segmentation is crucial in the development of an effective iris recognition system, it involves localizing relatively the exact region of the iris before its features are being extracted for matching. Several researches have used different algorithms for the segmentation of iris, however, traditional systems encounter challenges in accurately identifying individuals under varying conditions, primarily due to inaccurate segmentation. To address this, the study proposes an AI-based fusion technique combining Thresholding and Limbic Pupillary Boundary algorithms, aiming to enhance segmentation accuracy and reliability. Leveraging the eye images datasets from reputable sources and MATLAB implementation, the study improves segmentation performance, particularly in uncertain environments. The results are presented using histogram representation to demonstrate the efficacy of the fusion approach, contributing to advancements in iris recognition technology.