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Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images

Iris segmentation is a process to isolate the accurate iris region from the eye image for iris recognition. Iris segmentation on non-ideal and noisy iris images is accurate with active contour. Nevertheless, it is currently unclear on how active contour responds to blurry iris images or motion blur,...

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Main Authors: Jamaludin, Shahrizan, Mohamad Ayob, Ahmad Faisal, Mohd Norzeli, Syamimi, Mohamed, Saiful Bahri
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2022
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:https://repo.uum.edu.my/id/eprint/28744/1/JICT%2021%2003%202022%20411-435.pdf
https://doi.org/10.32890/jict2022.21.3.5
https://repo.uum.edu.my/id/eprint/28744/
https://e-journal.uum.edu.my/index.php/jict/article/view/15596
https://doi.org/10.32890/jict2022.21.3.5
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spelling my.uum.repo.287442023-02-08T01:21:41Z https://repo.uum.edu.my/id/eprint/28744/ Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images Jamaludin, Shahrizan Mohamad Ayob, Ahmad Faisal Mohd Norzeli, Syamimi Mohamed, Saiful Bahri TA Engineering (General). Civil engineering (General) Iris segmentation is a process to isolate the accurate iris region from the eye image for iris recognition. Iris segmentation on non-ideal and noisy iris images is accurate with active contour. Nevertheless, it is currently unclear on how active contour responds to blurry iris images or motion blur, which presents a significant obstacle in iris segmentation. Investigation on blurry iris images, especially on the initial contour position, is rarely published and must be clarified. Moreover, evolution or convergence speed remains a significant challenge for active contour as it segments the precise iris boundary. Therefore, this study carried out experiments to achieve an efficient iris segmentation algorithm in terms of accuracy and fast execution, according to the aforementioned concerns. In addition, initial contour was explored to clarify its position. In order to accomplish these goals, the Wiener filter and morphological closing were used for preprocessing and reflection removal. Next, the adaptive initial contour (AIC), δ, and stopping function were integrated to create the adaptive Chan-Vese active contour (ACVAC) algorithm. Finally, the partly -normalization method for normalization and feature extraction was designed by selecting the most prominent iris features. The findings revealed that the algorithm outperformed the other active contour-based approaches in computational time and segmentation accuracy. It proved that in blurry iris images, the accurate initial contour position could be established. This algorithm is significant to solve inaccurate segmentation on blurry iris images. Universiti Utara Malaysia Press 2022 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/28744/1/JICT%2021%2003%202022%20411-435.pdf Jamaludin, Shahrizan and Mohamad Ayob, Ahmad Faisal and Mohd Norzeli, Syamimi and Mohamed, Saiful Bahri (2022) Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images. Journal of Information and Communication Technology, 21 (03). pp. 411-435. ISSN 2180-3862 https://e-journal.uum.edu.my/index.php/jict/article/view/15596 https://doi.org/10.32890/jict2022.21.3.5 https://doi.org/10.32890/jict2022.21.3.5
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Jamaludin, Shahrizan
Mohamad Ayob, Ahmad Faisal
Mohd Norzeli, Syamimi
Mohamed, Saiful Bahri
Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
description Iris segmentation is a process to isolate the accurate iris region from the eye image for iris recognition. Iris segmentation on non-ideal and noisy iris images is accurate with active contour. Nevertheless, it is currently unclear on how active contour responds to blurry iris images or motion blur, which presents a significant obstacle in iris segmentation. Investigation on blurry iris images, especially on the initial contour position, is rarely published and must be clarified. Moreover, evolution or convergence speed remains a significant challenge for active contour as it segments the precise iris boundary. Therefore, this study carried out experiments to achieve an efficient iris segmentation algorithm in terms of accuracy and fast execution, according to the aforementioned concerns. In addition, initial contour was explored to clarify its position. In order to accomplish these goals, the Wiener filter and morphological closing were used for preprocessing and reflection removal. Next, the adaptive initial contour (AIC), δ, and stopping function were integrated to create the adaptive Chan-Vese active contour (ACVAC) algorithm. Finally, the partly -normalization method for normalization and feature extraction was designed by selecting the most prominent iris features. The findings revealed that the algorithm outperformed the other active contour-based approaches in computational time and segmentation accuracy. It proved that in blurry iris images, the accurate initial contour position could be established. This algorithm is significant to solve inaccurate segmentation on blurry iris images.
format Article
author Jamaludin, Shahrizan
Mohamad Ayob, Ahmad Faisal
Mohd Norzeli, Syamimi
Mohamed, Saiful Bahri
author_facet Jamaludin, Shahrizan
Mohamad Ayob, Ahmad Faisal
Mohd Norzeli, Syamimi
Mohamed, Saiful Bahri
author_sort Jamaludin, Shahrizan
title Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
title_short Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
title_full Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
title_fullStr Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
title_full_unstemmed Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images
title_sort adaptive initial contour and partly-normalization algorithm for iris segmentation of blurry iris images
publisher Universiti Utara Malaysia Press
publishDate 2022
url https://repo.uum.edu.my/id/eprint/28744/1/JICT%2021%2003%202022%20411-435.pdf
https://doi.org/10.32890/jict2022.21.3.5
https://repo.uum.edu.my/id/eprint/28744/
https://e-journal.uum.edu.my/index.php/jict/article/view/15596
https://doi.org/10.32890/jict2022.21.3.5
_version_ 1758580948660649984
score 13.211869

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