Towards more accurate iris recognition system by using hybrid approach for feature extraction along with classifier

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Ullah, Arif and Salam, Abdu and El-Raoui, Hanane and Sebai, Dorsaf and Rafie, Mahnaz (2022) Towards more accurate iris recognition system by using hybrid approach for feature extraction along with classifier. International Journal of Reconfigurable and Embedded Systems (IJRES), 11 (1). pp. 59-70. (https://doi.org/10.11591/ijres.v11.i1.pp59-70)

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Abstract

Iris recognition become one of the most accurate and reliable steadfast human biometric recognition system of the decad. This paper presents an accurate framework for iris recognition system using hybrid algorithm in preprocess and feature extraction section. The proposed model for iris recognition with significant feature extraction was divided into three main levels. First level is having pre-processing steps which are necessary for the desired tasks. Our model deploys on three types of datasets such as UBIRIS, CASIA, and MMU and gets optimal results for performing activity. At last, perform matching process with decision based classifier for iris recognition with acceptance or rejection rates. Experimental based results provide for analysis according to the false receipt rate and false refusal amount. In the third level, the error rate will be checked along with some statistical measures for final optimal results. Constructed on the outcome the planned method provided the most efficient effect as compared to the rest of the approach.

ORCID iDs

Ullah, Arif, Salam, Abdu, El-Raoui, Hanane ORCID logoORCID: https://orcid.org/0000-0002-9079-3248, Sebai, Dorsaf and Rafie, Mahnaz;
CORE (COnnecting REpositories)