2026-04-17T17:46:54.080Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:9218 2022-12-27T17:19:13Z 1

Frequency and Texture Features for Iris Recognition 2022 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/9218 https://ieeexplore.ieee.org/document/9983787 U. Tuba Е. Туба R. Capor Hrosik М. Туба M. Veinović Digital images and digital image processing have become a vital part of numerous applications, in every day life, science, security, health, etc. The iris of the human eye is a great biometric parameter that can be used for a person’s identification due to its richness and uniqueness in texture and other features. In this paper, a simple method based on the local binary pattern as a texture descriptor and frequency coefficients is proposed. After extracting the eye region, the iris region is found and features are calculated for that region of interest. A support vector machine is used for classification. The proposed method is tested on a well-known CASIA Interval-v4 dataset and the results are improved compared to methods that only use one of these features or a different set of features. conferenceObject 208 211 10.1109/TELFOR56187.2022.9983787 Proceedings of Papers