Vers l'utilisation d'un Treillis de Galois Fréquent pour la Reconnaissance de Symboles Graphiques
Identifieur interne : 001C04 ( Main/Exploration ); précédent : 001C03; suivant : 001C05Vers l'utilisation d'un Treillis de Galois Fréquent pour la Reconnaissance de Symboles Graphiques
Auteurs : Ameni Boumaiza [France] ; Salvatore Tabbone [France]Source :
Descripteurs français
- mix :
- Wicri :
- topic : Classification.
Abstract
The design of a graphics recognition method is a complex task due the multiplity of symbols and its configurations in real applications. In this paper, we propose a new approach based on a new concept called the Galois lattice which is often used for supervised recognition of graphical symbols. The originality of this paper is to build a concept lattice not in terms of all the features of symbols, but in terms of the most frequent or the most relevant ones. Our approach consists firstly, to build a visual vocabulary containing the frequent visual words from descriptors calculted on the symbols learning set. These visual vectors are calculated at the stable neighborhood of random points chosen from a given symbol. Secondly, we propose a new approach for symbol recognition based on a frequent Galois lattice. The concept lattice obtained based on frequent patterns is trained and used as a supervised classifier for symbols. The experimental results show recognition capabilities of our method and its robustness to noise.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
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- to stream Hal, to step Checkpoint: 001826
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- to stream Main, to step Curation: 001C04
Le document en format XML
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<front><div type="abstract" xml:lang="en">The design of a graphics recognition method is a complex task due the multiplity of symbols and its configurations in real applications. In this paper, we propose a new approach based on a new concept called the Galois lattice which is often used for supervised recognition of graphical symbols. The originality of this paper is to build a concept lattice not in terms of all the features of symbols, but in terms of the most frequent or the most relevant ones. Our approach consists firstly, to build a visual vocabulary containing the frequent visual words from descriptors calculted on the symbols learning set. These visual vectors are calculated at the stable neighborhood of random points chosen from a given symbol. Secondly, we propose a new approach for symbol recognition based on a frequent Galois lattice. The concept lattice obtained based on frequent patterns is trained and used as a supervised classifier for symbols. The experimental results show recognition capabilities of our method and its robustness to noise.</div>
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{{Explor lien |wiki= Wicri/Lorraine |area= InforLorV4 |flux= Main |étape= Exploration |type= RBID |clé= Hal:hal-00662559 |texte= Vers l'utilisation d'un Treillis de Galois Fréquent pour la Reconnaissance de Symboles Graphiques }}
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