A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images

Iris segmentation in the iris recognition systems is a challenging task under noncooperative environments. The iris segmentation is a process of detecting the pupil, iris’s outer boundary, and eyelids in the iris image. In this paper, we propose a pupil localization method for locating the pupils in...

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Main Authors: Vineet Kumar, Abhijit Asati, Anu Gupta
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2016/4709876
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author Vineet Kumar
Abhijit Asati
Anu Gupta
author_facet Vineet Kumar
Abhijit Asati
Anu Gupta
author_sort Vineet Kumar
collection DOAJ
description Iris segmentation in the iris recognition systems is a challenging task under noncooperative environments. The iris segmentation is a process of detecting the pupil, iris’s outer boundary, and eyelids in the iris image. In this paper, we propose a pupil localization method for locating the pupils in the non-close-up and frontal-view iris images that are captured under near-infrared (NIR) illuminations and contain the noise, such as specular and lighting reflection spots, eyeglasses, nonuniform illumination, low contrast, and occlusions by the eyelids, eyelashes, and eyebrow hair. In the proposed method, first, a novel edge-map is created from the iris image, which is based on combining the conventional thresholding and edge detection based segmentation techniques, and then, the general circular Hough transform (CHT) is used to find the pupil circle parameters in the edge-map. Our main contribution in this research is a novel edge-map creation technique, which reduces the false edges drastically in the edge-map of the iris image and makes the pupil localization in the noisy NIR images more accurate, fast, robust, and simple. The proposed method was tested with three iris databases: CASIA-Iris-Thousand (version 4.0), CASIA-Iris-Lamp (version 3.0), and MMU (version 2.0). The average accuracy of the proposed method is 99.72% and average time cost per image is 0.727 sec.
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spelling doaj-art-9b79af8e66294da7bfd38a7537b328672025-02-03T05:44:37ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552016-01-01201610.1155/2016/47098764709876A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris ImagesVineet Kumar0Abhijit Asati1Anu Gupta2Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani 333031, IndiaDepartment of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani 333031, IndiaDepartment of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani 333031, IndiaIris segmentation in the iris recognition systems is a challenging task under noncooperative environments. The iris segmentation is a process of detecting the pupil, iris’s outer boundary, and eyelids in the iris image. In this paper, we propose a pupil localization method for locating the pupils in the non-close-up and frontal-view iris images that are captured under near-infrared (NIR) illuminations and contain the noise, such as specular and lighting reflection spots, eyeglasses, nonuniform illumination, low contrast, and occlusions by the eyelids, eyelashes, and eyebrow hair. In the proposed method, first, a novel edge-map is created from the iris image, which is based on combining the conventional thresholding and edge detection based segmentation techniques, and then, the general circular Hough transform (CHT) is used to find the pupil circle parameters in the edge-map. Our main contribution in this research is a novel edge-map creation technique, which reduces the false edges drastically in the edge-map of the iris image and makes the pupil localization in the noisy NIR images more accurate, fast, robust, and simple. The proposed method was tested with three iris databases: CASIA-Iris-Thousand (version 4.0), CASIA-Iris-Lamp (version 3.0), and MMU (version 2.0). The average accuracy of the proposed method is 99.72% and average time cost per image is 0.727 sec.http://dx.doi.org/10.1155/2016/4709876
spellingShingle Vineet Kumar
Abhijit Asati
Anu Gupta
A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
Journal of Electrical and Computer Engineering
title A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
title_full A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
title_fullStr A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
title_full_unstemmed A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
title_short A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images
title_sort novel edge map creation approach for highly accurate pupil localization in unconstrained infrared iris images
url http://dx.doi.org/10.1155/2016/4709876
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