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Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform

The automatic detection of bilateral symmetry is a challenging task in computer vision and pattern recognition. This paper presents an approach for the detection of bilateral symmetry in digital single object images. Our method relies on the extraction of Scale Invariant Feature Transform (SIFT) bas...

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Detalles Bibliográficos
Autores principales: Akbar, Habib, Hayat, Khizar, Haq, Nuhman ul, Bajwa, Usama Ijaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140689/
https://www.ncbi.nlm.nih.gov/pubmed/25144655
http://dx.doi.org/10.1371/journal.pone.0103561
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author Akbar, Habib
Hayat, Khizar
Haq, Nuhman ul
Bajwa, Usama Ijaz
author_facet Akbar, Habib
Hayat, Khizar
Haq, Nuhman ul
Bajwa, Usama Ijaz
author_sort Akbar, Habib
collection PubMed
description The automatic detection of bilateral symmetry is a challenging task in computer vision and pattern recognition. This paper presents an approach for the detection of bilateral symmetry in digital single object images. Our method relies on the extraction of Scale Invariant Feature Transform (SIFT) based feature points, which serves as the basis for the ascertainment of the centroid of the object; the latter being the origin under the Cartesian coordinate system to be converted to the polar coordinate system in order to facilitate the selection symmetric coordinate pairs. This is followed by comparing the gradient magnitude and orientation of the corresponding points to evaluate the amount of symmetry exhibited by each pair of points. The experimental results show that our approach draw the symmetry line accurately, provided that the observed centroid point is true.
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spelling pubmed-41406892014-08-25 Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform Akbar, Habib Hayat, Khizar Haq, Nuhman ul Bajwa, Usama Ijaz PLoS One Research Article The automatic detection of bilateral symmetry is a challenging task in computer vision and pattern recognition. This paper presents an approach for the detection of bilateral symmetry in digital single object images. Our method relies on the extraction of Scale Invariant Feature Transform (SIFT) based feature points, which serves as the basis for the ascertainment of the centroid of the object; the latter being the origin under the Cartesian coordinate system to be converted to the polar coordinate system in order to facilitate the selection symmetric coordinate pairs. This is followed by comparing the gradient magnitude and orientation of the corresponding points to evaluate the amount of symmetry exhibited by each pair of points. The experimental results show that our approach draw the symmetry line accurately, provided that the observed centroid point is true. Public Library of Science 2014-08-21 /pmc/articles/PMC4140689/ /pubmed/25144655 http://dx.doi.org/10.1371/journal.pone.0103561 Text en © 2014 Akbar et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Akbar, Habib
Hayat, Khizar
Haq, Nuhman ul
Bajwa, Usama Ijaz
Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title_full Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title_fullStr Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title_full_unstemmed Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title_short Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform
title_sort bilateral symmetry detection on the basis of scale invariant feature transform
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140689/
https://www.ncbi.nlm.nih.gov/pubmed/25144655
http://dx.doi.org/10.1371/journal.pone.0103561
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