A novel palmprint segmentation technique
Recent paradigm shift from the conventional contact based palmprint recognition to contactless based systems (CBS) has necessitated the development of a variety of these systems. A major challenge of these systems is it robustness to illumination variation in unconstrained environment, thus making s...
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Online Access: | http://irep.iium.edu.my/7227/ http://irep.iium.edu.my/7227/ http://irep.iium.edu.my/7227/1/A_NOVEL_PALMPRINT_SEGMENTATION_TECHNIQUE.pdf http://irep.iium.edu.my/7227/4/06141677.pdf |
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iium-72272012-04-20T07:44:06Z http://irep.iium.edu.my/7227/ A novel palmprint segmentation technique Rotinwa-Akinbile, M. O. Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka T Technology (General) Recent paradigm shift from the conventional contact based palmprint recognition to contactless based systems (CBS) has necessitated the development of a variety of these systems. A major challenge of these systems is it robustness to illumination variation in unconstrained environment, thus making segmentation difficult. In this paper, the acquired image undergoes color space conversion and the output is filtered using coefficients obtained from the training of an artificial neural network (ANN) based model coefficient determination technique. Performance analysis of the proposed technique shows better performance in term of mean square error, true positive rate and accuracy when compared with two other techniques. Furthermore, it has also been observed that the proposed method is illumination invariant hence its suitability for deployment in contactless palmprint recognition systems. 2011-12-12 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/7227/1/A_NOVEL_PALMPRINT_SEGMENTATION_TECHNIQUE.pdf application/pdf en http://irep.iium.edu.my/7227/4/06141677.pdf Rotinwa-Akinbile, M. O. and Aibinu, Abiodun Musa and Salami, Momoh Jimoh Emiyoka (2011) A novel palmprint segmentation technique. In: 1st International Conference on Informatics and Computational Intelligence (ICI 2011), 12-14 December 2011, Parahyangan Catholic University, Bandung, Indonesia. http://ici2011.info/ |
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T Technology (General) |
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T Technology (General) Rotinwa-Akinbile, M. O. Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka A novel palmprint segmentation technique |
description |
Recent paradigm shift from the conventional contact based palmprint recognition to contactless based systems (CBS) has necessitated the development of a variety of these systems. A major challenge of these systems is it robustness to illumination variation in unconstrained environment, thus making segmentation difficult. In this paper, the acquired image undergoes color space conversion and the output is filtered using coefficients obtained from the training of an artificial neural network (ANN) based model coefficient determination technique. Performance analysis of the proposed technique shows better performance in term of mean square error, true positive rate and accuracy when compared with two other techniques. Furthermore, it has also been observed that the proposed method is illumination invariant hence its suitability for deployment in contactless palmprint recognition systems. |
format |
Conference or Workshop Item |
author |
Rotinwa-Akinbile, M. O. Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka |
author_facet |
Rotinwa-Akinbile, M. O. Aibinu, Abiodun Musa Salami, Momoh Jimoh Emiyoka |
author_sort |
Rotinwa-Akinbile, M. O. |
title |
A novel palmprint segmentation technique |
title_short |
A novel palmprint segmentation technique |
title_full |
A novel palmprint segmentation technique |
title_fullStr |
A novel palmprint segmentation technique |
title_full_unstemmed |
A novel palmprint segmentation technique |
title_sort |
novel palmprint segmentation technique |
publishDate |
2011 |
url |
http://irep.iium.edu.my/7227/ http://irep.iium.edu.my/7227/ http://irep.iium.edu.my/7227/1/A_NOVEL_PALMPRINT_SEGMENTATION_TECHNIQUE.pdf http://irep.iium.edu.my/7227/4/06141677.pdf |
first_indexed |
2023-09-18T20:16:31Z |
last_indexed |
2023-09-18T20:16:31Z |
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1777407824333111296 |