| DOI | Trouver le DOI : https://doi.org/10.1109/ICCAT.2013.6522006 |
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| Auteur | Rechercher : Salhi, A.I.; Rechercher : Kardouchi, M.; Rechercher : Belacel, N.1 |
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| Affiliation | - Conseil national de recherches du Canada. Institut de technologie de l'information du CNRC
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| Format | Texte, Article |
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| Conférence | 2013 International Conference on Computer Applications Technology, ICCAT 2013, 20 January 2013 through 22 January 2013, Sousse |
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| Sujet | Dimensional vectors; Feature dimensions; Feature vectors; HFOG; High dimensional feature; Histogram of oriented gradients (HOG); HOG; Oriented gradients; Computer applications; Fuzzy sets; Graphic methods; Statistical methods; Face recognition |
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| Résumé | Efficient face descriptors require a careful equilibration between accuracy and feature dimension. In recent years Histogram of Oriented Gradient (HOG) starts to be used in the face recognition task. However the best recognition rate for HOG requires a high dimensional feature. In this paper, we will incorporate fuzzy concept to HOG aiming to achieve a good recognition rate with a low feature vector dimension. The proposed Histogram of Fuzzy Oriented Gradient is applied to the face recognition task. Experimental results on ORL database have demonstrated that HFOG outperforms the original HOG with a lower dimensional vector. © 2013 IEEE. |
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| Date de publication | 2013 |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Numéro NPARC | 21269730 |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | e488d603-ebe2-47c6-98c1-b0c84f31a721 |
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| Enregistrement créé | 2013-12-13 |
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| Enregistrement modifié | 2020-04-22 |
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