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Gender Classification Based on Geometry Features of Palm Image

This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other...

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Detalles Bibliográficos
Autores principales: Wu, Ming, Yuan, Yubo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032673/
https://www.ncbi.nlm.nih.gov/pubmed/24892081
http://dx.doi.org/10.1155/2014/734564
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author Wu, Ming
Yuan, Yubo
author_facet Wu, Ming
Yuan, Yubo
author_sort Wu, Ming
collection PubMed
description This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other one is classification system with polynomial smooth support vector machine (PSSVM). A total of 180 palm images were collected from 30 persons to verify the validity of the proposed gender classification approach and the results are satisfactory with classification rate over 85%. Experimental results demonstrate that our proposed approach is feasible and effective in gender recognition.
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spelling pubmed-40326732014-06-02 Gender Classification Based on Geometry Features of Palm Image Wu, Ming Yuan, Yubo ScientificWorldJournal Research Article This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other one is classification system with polynomial smooth support vector machine (PSSVM). A total of 180 palm images were collected from 30 persons to verify the validity of the proposed gender classification approach and the results are satisfactory with classification rate over 85%. Experimental results demonstrate that our proposed approach is feasible and effective in gender recognition. Hindawi Publishing Corporation 2014 2014-04-29 /pmc/articles/PMC4032673/ /pubmed/24892081 http://dx.doi.org/10.1155/2014/734564 Text en Copyright © 2014 M. Wu and Y. Yuan. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wu, Ming
Yuan, Yubo
Gender Classification Based on Geometry Features of Palm Image
title Gender Classification Based on Geometry Features of Palm Image
title_full Gender Classification Based on Geometry Features of Palm Image
title_fullStr Gender Classification Based on Geometry Features of Palm Image
title_full_unstemmed Gender Classification Based on Geometry Features of Palm Image
title_short Gender Classification Based on Geometry Features of Palm Image
title_sort gender classification based on geometry features of palm image
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032673/
https://www.ncbi.nlm.nih.gov/pubmed/24892081
http://dx.doi.org/10.1155/2014/734564
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