Title: Iris recognition system using deep learning techniques
Authors: Amer A. Sallam; Hadeel Al Amery; Ahmed Y.A. Saeed
Addresses: Computer Networks and Distributed Systems Department, Faculty of Engineering and IT, Taiz University, Taiz, Yemen ' Department of Information Technology, Faculty of Engineering and IT, Taiz University, Taiz, Yemen ' Department of Software Engineering, Faculty of Engineering and IT, Taiz University, Taiz, Yemen
Abstract: Deep learning has been used and demonstrated intensively as a vital technique in data mining that can accurately and effectively evaluate enormous amounts of data for various applications. Iris recognition is one of those applications that necessitate complex algorithms for analysing and perfectly detecting the hidden patterns among its data in order to effectively distinguish one person from another. In this paper, an iris recognition system based on various deep learning techniques has been proposed. Through many experiments that were conducted on CASIA-V1 and ATVS datasets, the proposed system based on the Xception model was able to achieve significant results with 99.9% accuracy on CASIA-V1 dataset.
Keywords: biometrics; deep learning; transfer learning; segmentation.
International Journal of Biometrics, 2023 Vol.15 No.6, pp.705 - 725
Received: 18 Jan 2022
Accepted: 29 Aug 2022
Published online: 06 Oct 2023 *