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Extrema Points Application In Determining Iris Region Of Interest

Extrema points are usually applied to solve everyday problems, for example, to determine the potential of a created tool and for optimisation. In this study, extrema points were used to help determine the region of interest (ROI) for the iris in iris recognition systems. Iris recognitionis an...

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Main Authors: Othman, Zuraini, Kasmin, Fauziah, Syed Ahmad, Sharifah Sakinah, Abdullah, Azizi
Format: Article
Language:English
Published: 2019
Online Access:http://eprints.utem.edu.my/id/eprint/24465/2/2368-ARTICLE%20TEXT-5205-1-10-20190731.PDF
http://eprints.utem.edu.my/id/eprint/24465/
https://ejournal.upsi.edu.my/index.php/EJSMT/article/view/2368/1982
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spelling my.utem.eprints.244652020-12-03T16:22:24Z http://eprints.utem.edu.my/id/eprint/24465/ Extrema Points Application In Determining Iris Region Of Interest Othman, Zuraini Kasmin, Fauziah Syed Ahmad, Sharifah Sakinah Abdullah, Azizi Extrema points are usually applied to solve everyday problems, for example, to determine the potential of a created tool and for optimisation. In this study, extrema points were used to help determine the region of interest (ROI) for the iris in iris recognition systems. Iris recognitionis an automated method of biometric identification that uses mathematical pattern-recognition techniques on the images of one or both irises of an individual' seyes, where the complex patterns are unique, stable, and can be seen from a distance. In order to obtain accurate results, the iris must be localised correctly. Hence, to address this issue, this paper proposed a method of iris localisation in the case of ideal and non-ideal iris images. In this study, the algorithm was based on finding the classification for the region of interest (ROI) with the help of a Support Vector Machine (SVM) by applying a histogram of grey level values as a descriptor in each region from the region growing technique. The valid ROI was found from the probabilities graph of the SVM obtained by looking at the global minimum conditions determined by a second derivative model in a graph of functions. Furthermore, the model from the global minimum condition values was used in the test phase, and the results showed that the ROI image obtained helped in the elimination of sensitive noise with the involvement of fewer computations, while reserving relevant information. 2019-06 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24465/2/2368-ARTICLE%20TEXT-5205-1-10-20190731.PDF Othman, Zuraini and Kasmin, Fauziah and Syed Ahmad, Sharifah Sakinah and Abdullah, Azizi (2019) Extrema Points Application In Determining Iris Region Of Interest. Educatum Journal Of Science, Mathematics And Technology (EJSMT), 6 (1). pp. 35-40. ISSN 2289-7070 https://ejournal.upsi.edu.my/index.php/EJSMT/article/view/2368/1982 10.37134/ejsmt.vol6.1.5.2019
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Extrema points are usually applied to solve everyday problems, for example, to determine the potential of a created tool and for optimisation. In this study, extrema points were used to help determine the region of interest (ROI) for the iris in iris recognition systems. Iris recognitionis an automated method of biometric identification that uses mathematical pattern-recognition techniques on the images of one or both irises of an individual' seyes, where the complex patterns are unique, stable, and can be seen from a distance. In order to obtain accurate results, the iris must be localised correctly. Hence, to address this issue, this paper proposed a method of iris localisation in the case of ideal and non-ideal iris images. In this study, the algorithm was based on finding the classification for the region of interest (ROI) with the help of a Support Vector Machine (SVM) by applying a histogram of grey level values as a descriptor in each region from the region growing technique. The valid ROI was found from the probabilities graph of the SVM obtained by looking at the global minimum conditions determined by a second derivative model in a graph of functions. Furthermore, the model from the global minimum condition values was used in the test phase, and the results showed that the ROI image obtained helped in the elimination of sensitive noise with the involvement of fewer computations, while reserving relevant information.
format Article
author Othman, Zuraini
Kasmin, Fauziah
Syed Ahmad, Sharifah Sakinah
Abdullah, Azizi
spellingShingle Othman, Zuraini
Kasmin, Fauziah
Syed Ahmad, Sharifah Sakinah
Abdullah, Azizi
Extrema Points Application In Determining Iris Region Of Interest
author_facet Othman, Zuraini
Kasmin, Fauziah
Syed Ahmad, Sharifah Sakinah
Abdullah, Azizi
author_sort Othman, Zuraini
title Extrema Points Application In Determining Iris Region Of Interest
title_short Extrema Points Application In Determining Iris Region Of Interest
title_full Extrema Points Application In Determining Iris Region Of Interest
title_fullStr Extrema Points Application In Determining Iris Region Of Interest
title_full_unstemmed Extrema Points Application In Determining Iris Region Of Interest
title_sort extrema points application in determining iris region of interest
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24465/2/2368-ARTICLE%20TEXT-5205-1-10-20190731.PDF
http://eprints.utem.edu.my/id/eprint/24465/
https://ejournal.upsi.edu.my/index.php/EJSMT/article/view/2368/1982
_version_ 1687397236980318208
score 13.211869

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