Face recognition using Angular Radial Transform

Moment-based Angular Radial Transform, Legendre moment invariants and Zernike moments are a family of orthogonal functions which allow the generation of non-redundant descriptors by the projection of an image onto an orthogonal basis. These descriptors can be used for classification, such as in face...

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Main Authors: Bensenane Hamdan, Keche Mokhtar
Format: Article
Language:English
Published: Elsevier 2018-04-01
Series:Journal of King Saud University: Computer and Information Sciences
Online Access:http://www.sciencedirect.com/science/article/pii/S131915781630129X
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spelling doaj-ccbe27d35001419aa787be35cd84575c2020-11-24T22:39:35ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782018-04-01302141151Face recognition using Angular Radial TransformBensenane Hamdan0Keche Mokhtar1Corresponding author.; Laboratoire Signals and Images, Dept. of Electronique, Université des Sciences et de la Technologie d’Oran Mohamed Boudiaf, USTO-MB, BP 1505, 3100 Oran, AlgeriaLaboratoire Signals and Images, Dept. of Electronique, Université des Sciences et de la Technologie d’Oran Mohamed Boudiaf, USTO-MB, BP 1505, 3100 Oran, AlgeriaMoment-based Angular Radial Transform, Legendre moment invariants and Zernike moments are a family of orthogonal functions which allow the generation of non-redundant descriptors by the projection of an image onto an orthogonal basis. These descriptors can be used for classification, such as in face recognition. Zernike moments and Legendre moments have already been used for this purpose.This paper proposes to use moment-based Angular Radial Transform for extracting the face characteristics that feed a Support Vector Machine or a Nearest Neighbor Classifier for face recognition. Facial images from the ORL database, Essex Faces94 database, Essex Faces96 database, and Yale database were used for testing the proposed approach. The experimental results obtained show that the proposed method is more efficient, in terms of recognition rate, than the methods based on Zernike and Legendre moments. It is also found that its performance is comparable to that of the best state-of-the-arts methods. Keywords: Angular Radial Transform (ART), Legendre moment invariants (LMI), Euclidean distance (ED), Pseudo-Zernike moments (PZM), Nearest Neighbor Classifier (NNC), Support Vector Machines (SVM)http://www.sciencedirect.com/science/article/pii/S131915781630129X
collection DOAJ
language English
format Article
sources DOAJ
author Bensenane Hamdan
Keche Mokhtar
spellingShingle Bensenane Hamdan
Keche Mokhtar
Face recognition using Angular Radial Transform
Journal of King Saud University: Computer and Information Sciences
author_facet Bensenane Hamdan
Keche Mokhtar
author_sort Bensenane Hamdan
title Face recognition using Angular Radial Transform
title_short Face recognition using Angular Radial Transform
title_full Face recognition using Angular Radial Transform
title_fullStr Face recognition using Angular Radial Transform
title_full_unstemmed Face recognition using Angular Radial Transform
title_sort face recognition using angular radial transform
publisher Elsevier
series Journal of King Saud University: Computer and Information Sciences
issn 1319-1578
publishDate 2018-04-01
description Moment-based Angular Radial Transform, Legendre moment invariants and Zernike moments are a family of orthogonal functions which allow the generation of non-redundant descriptors by the projection of an image onto an orthogonal basis. These descriptors can be used for classification, such as in face recognition. Zernike moments and Legendre moments have already been used for this purpose.This paper proposes to use moment-based Angular Radial Transform for extracting the face characteristics that feed a Support Vector Machine or a Nearest Neighbor Classifier for face recognition. Facial images from the ORL database, Essex Faces94 database, Essex Faces96 database, and Yale database were used for testing the proposed approach. The experimental results obtained show that the proposed method is more efficient, in terms of recognition rate, than the methods based on Zernike and Legendre moments. It is also found that its performance is comparable to that of the best state-of-the-arts methods. Keywords: Angular Radial Transform (ART), Legendre moment invariants (LMI), Euclidean distance (ED), Pseudo-Zernike moments (PZM), Nearest Neighbor Classifier (NNC), Support Vector Machines (SVM)
url http://www.sciencedirect.com/science/article/pii/S131915781630129X
work_keys_str_mv AT bensenanehamdan facerecognitionusingangularradialtransform
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