Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali

Iris recognition is reckoned as one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Techniqu...

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Main Author:	M. Ali, Musab A.
Format:	Thesis
Language:	English
Published:	2016
Subjects:	Scanning systems Optical fibers
Online Access:	http://ir.uitm.edu.my/id/eprint/21546/ http://ir.uitm.edu.my/id/eprint/21546/1/TP_MUSAB%20A.M.%20ALI%20EE%2016_5.pdf

id	uitm-21546
recordtype	eprints
spelling	uitm-215462018-10-01T08:35:22Z http://ir.uitm.edu.my/id/eprint/21546/ Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali M. Ali, Musab A. Scanning systems Optical fibers Iris recognition is reckoned as one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Technique (FPM) specifically in getting the actual center of the pupil with high level of accuracy prior to iris localization task, followed by a particular enhancement in iris normalization that is the application of quarter size of an iris image (instead of processing a whole or half size of an iris image) and for better precision and faster recognition with the robust Support Vector Machine (SVM) as classifier. Further aim of this research is the integration of cancelable biometrics feature in the proposed iris recognition technique via non-invertible transformation which determines the feature transformation-based template protection techniques security. Therefore, it is significant to formulate the non-invertibility measure to circumvent the possibility of adversary having the capability in guessing the original biometric providing that the transformed template is obtained. At any process of recognition stage, the biometric data is protected and also whenever there is a compromise to any information in the database it will be on the cancelable biometric template merely without affecting the original biometric information. In order to evaluate and verify the effectiveness of the proposed technique, CASIA-A (version 3.1) and Bath-A iris databases have been selected for performance testing. Briefly, the processes of the iris recognition system proposed in this research work are locating the pupil first via the novel technique that is the Fusion of Profile and Mask (FPM) Technique focusing on getting the actual center of the pupil then followed by localizing the actual iris region with the circular Hough transform. Next, select smaller yet optimal and effective normalized iris image size by applying different normalization factors. Instead of processing a whole or half size of an iris image, the 480 code size which is equivalent to the quarter size of an iris is selected due to its outstandingly accurate results and less computational complexity. The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. The experimental results showed that the recognition rate achieved are of 99.9% on Bath-A data set, with a maximum decision criterion of 0.97. 2016 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/21546/1/TP_MUSAB%20A.M.%20ALI%20EE%2016_5.pdf M. Ali, Musab A. (2016) Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali. PhD thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Scanning systems Optical fibers
spellingShingle	Scanning systems Optical fibers M. Ali, Musab A. Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
description	Iris recognition is reckoned as one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Technique (FPM) specifically in getting the actual center of the pupil with high level of accuracy prior to iris localization task, followed by a particular enhancement in iris normalization that is the application of quarter size of an iris image (instead of processing a whole or half size of an iris image) and for better precision and faster recognition with the robust Support Vector Machine (SVM) as classifier. Further aim of this research is the integration of cancelable biometrics feature in the proposed iris recognition technique via non-invertible transformation which determines the feature transformation-based template protection techniques security. Therefore, it is significant to formulate the non-invertibility measure to circumvent the possibility of adversary having the capability in guessing the original biometric providing that the transformed template is obtained. At any process of recognition stage, the biometric data is protected and also whenever there is a compromise to any information in the database it will be on the cancelable biometric template merely without affecting the original biometric information. In order to evaluate and verify the effectiveness of the proposed technique, CASIA-A (version 3.1) and Bath-A iris databases have been selected for performance testing. Briefly, the processes of the iris recognition system proposed in this research work are locating the pupil first via the novel technique that is the Fusion of Profile and Mask (FPM) Technique focusing on getting the actual center of the pupil then followed by localizing the actual iris region with the circular Hough transform. Next, select smaller yet optimal and effective normalized iris image size by applying different normalization factors. Instead of processing a whole or half size of an iris image, the 480 code size which is equivalent to the quarter size of an iris is selected due to its outstandingly accurate results and less computational complexity. The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. The experimental results showed that the recognition rate achieved are of 99.9% on Bath-A data set, with a maximum decision criterion of 0.97.
format	Thesis
author	M. Ali, Musab A.
author_facet	M. Ali, Musab A.
author_sort	M. Ali, Musab A.
title	Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
title_short	Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
title_full	Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
title_fullStr	Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
title_full_unstemmed	Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
title_sort	biometric identification and recognition for iris using failure rejection rate (frr) / musab a. m. ali
publishDate	2016
url	http://ir.uitm.edu.my/id/eprint/21546/ http://ir.uitm.edu.my/id/eprint/21546/1/TP_MUSAB%20A.M.%20ALI%20EE%2016_5.pdf
first_indexed	2023-09-18T23:06:48Z
last_indexed	2023-09-18T23:06:48Z
_version_	1777418536820408320

Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali

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