A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters

This article suggests an enhancement of the Masek circle model approach usually used to find a trade-off between modeling complexity, algorithm accuracy, and computational time, mainly for embedded systems where the real-time aspect is a high challenge. Moreover, most commercialized systems (Aoptix,...

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Main Authors: Aydi Walid, Fadhel Nade, Masmoudi Nouri, Kamoun Lotfi
Format: Article
Language:English
Published: De Gruyter 2015-06-01
Series:Journal of Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1515/jisys-2014-0109
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author Aydi Walid
Fadhel Nade
Masmoudi Nouri
Kamoun Lotfi
author_facet Aydi Walid
Fadhel Nade
Masmoudi Nouri
Kamoun Lotfi
author_sort Aydi Walid
collection DOAJ
description This article suggests an enhancement of the Masek circle model approach usually used to find a trade-off between modeling complexity, algorithm accuracy, and computational time, mainly for embedded systems where the real-time aspect is a high challenge. Moreover, most commercialized systems (Aoptix, Mkc-series, IriScan, etc.) today frame iris regions by circles. This work led to several novelties: first, in the segmentation process, the corneal reflection removal method based on morphological reconstruction and pixel connectivity was implemented. Second, the picture size reduction was applied according to nearest-neighbor interpolation. Third, the image gradient of the convolved-reduced picture was then generated using four proposed matrices. Fourth, and to reduce the complexity of the traditional method for the detection of the top and lower eyelids, a new method based on the Radon transform and the least squares fitting method was applied. Fifth, eyelashes were detected via the diagonal gradient and thresholding method. Monogenic signal was used in the feature extraction process. Finally, two distance measures were selected as a metric for recognition. Our experimental results using CASIA iris database V3.0 reveal that the proposed method provides a high performance in terms of speed and accuracy. Using dissimilarity modified Hamming distance, the accuracy of iris recognition was improved, with a false acceptance rate equal to 3% and a speed at least eight times as compared with the state of the art.
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spelling doaj.art-d9a21d6d521847bb862dbc975c0c741e2022-12-21T21:33:50ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2015-06-0124216117910.1515/jisys-2014-0109A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor FiltersAydi Walid0Fadhel Nade1Masmoudi Nouri2Kamoun Lotfi3Laboratory of Electronics and Information Technologies, University of Sfax, TunisiaMobile Services & Software Engineering Group, University of Hamburg, GermanyLaboratory of Electronics and Information Technologies, University of Sfax, TunisiaLaboratory of Electronics and Information Technologies, University of Sfax, TunisiaThis article suggests an enhancement of the Masek circle model approach usually used to find a trade-off between modeling complexity, algorithm accuracy, and computational time, mainly for embedded systems where the real-time aspect is a high challenge. Moreover, most commercialized systems (Aoptix, Mkc-series, IriScan, etc.) today frame iris regions by circles. This work led to several novelties: first, in the segmentation process, the corneal reflection removal method based on morphological reconstruction and pixel connectivity was implemented. Second, the picture size reduction was applied according to nearest-neighbor interpolation. Third, the image gradient of the convolved-reduced picture was then generated using four proposed matrices. Fourth, and to reduce the complexity of the traditional method for the detection of the top and lower eyelids, a new method based on the Radon transform and the least squares fitting method was applied. Fifth, eyelashes were detected via the diagonal gradient and thresholding method. Monogenic signal was used in the feature extraction process. Finally, two distance measures were selected as a metric for recognition. Our experimental results using CASIA iris database V3.0 reveal that the proposed method provides a high performance in terms of speed and accuracy. Using dissimilarity modified Hamming distance, the accuracy of iris recognition was improved, with a false acceptance rate equal to 3% and a speed at least eight times as compared with the state of the art.https://doi.org/10.1515/jisys-2014-0109feature extractionmonogenic filtersfractal analysis2d log-gabor
spellingShingle Aydi Walid
Fadhel Nade
Masmoudi Nouri
Kamoun Lotfi
A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
Journal of Intelligent Systems
feature extraction
monogenic filters
fractal analysis
2d log-gabor
title A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
title_full A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
title_fullStr A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
title_full_unstemmed A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
title_short A Robust Iris Feature Extraction Approach Based on Monogenic and 2D Log-Gabor Filters
title_sort robust iris feature extraction approach based on monogenic and 2d log gabor filters
topic feature extraction
monogenic filters
fractal analysis
2d log-gabor
url https://doi.org/10.1515/jisys-2014-0109
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