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A new approach of iris detection and recognition.

Biswas, Rubel; Uddin, Jia; Hasan, Md. Junayed

Authors

Rubel Biswas

Jia Uddin



Abstract

This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: Segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen's Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.

Citation

BISWAS, R., UDDIN, J. and HASAN, M.J. 2017. A new approach of iris detection and recognition. International journal of electrical and computer engineering (IJECE) [online], 7(5), pages 2530-2536. Available from: http://doi.org/10.11591/ijece.v7i5.pp2530-2536

Journal Article Type Article
Acceptance Date Sep 11, 2017
Online Publication Date Oct 31, 2017
Publication Date Oct 31, 2017
Deposit Date Oct 26, 2023
Publicly Available Date Feb 5, 2024
Journal International journal of electrical and computer engineering (IJECE)
Print ISSN 2088-8708
Electronic ISSN 2722-2578
Publisher Institute of Advanced Engineering and Science
Peer Reviewed Peer Reviewed
Volume 7
Issue 5
Pages 2530-2536
DOI https://doi.org/10.11591/ijece.v7i5.pp2530-2536
Keywords Daugman’s rubber sheet; DNS (dominant neighborhood structure); E-secuirity; GNS (global neighborhood structure); Iris recognition
Public URL https://rgu-repository.worktribe.com/output/2093172

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