ARTIFICIAL INTELLIGENCE BASED IRIS SEGMENTATION

Abstract

The iris, a colored component of the eye surrounding the pupil, possesses a unique and distinctive pattern for each individual. Iris segmentation plays a pivotal role in the field of biometric. It serves as a critical stage in iris recognition systems, separating the iris area from other parts of the eye image, thereby enhancing the effectiveness of subsequent stages. In this paper, we propose a fusion-based iris segmentation technique that combines Thresholding and Limbic Pupil Boundary (LPB) methods. We evaluate the robustness of our approach using the CASIA and Ayush datasets. Specifically, we perform a comparative analysis on the Ayush dataset, comprising 650 eye images. The results of the evaluation demonstrate that the proposed approach accurately segments the iris from the eye image, laying the foundation for a reliable recognition system