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Reconnaissance et localisation de symboles dans les documents graphiques : approches basées sur le treillis de concepts

Abstract : Computer vision is a field that includes methods for the acquisition, processing, analysis and understanding of images to produce numerical or symbolic information. A research contributing to the development of this area is to replicate the capabilities of human vision to perceive and understand images. Our thesis is part of this research axis. We propose several original contributions belonging to the context of graphics recognition and spotting context. The originality of the proposed approaches is the proposal of an interesting alliance between the Formal Concept Analysis and the Computer Vision fields. We face the study of the FCA field and more precisely the adaptation of the structure of concept lattice and its use as the main tool of our work. The main feature of our work lies in its generic aspect because the proposed methods can be combined with various other tools keeping the same strategies and following a similar procedure. Our foray into the area of the Formal Concept Analysis and more precisely our choice of the structure of the Galois lattice, also called concept lattice is motivated by the many advantages offered by this tool. The main advantage of concept lattice is the symbolic aspect. It is a concise, accurate and flexible search space thus facilitating decision making. Our contributions are recorded as part of the recognition and localization of symbols in graphic documents. We propose to recognize and spot symbols in graphical documents (technical drawings for example) using the alliance between the bag of words representation and the Galois lattice formalism. We opt for various methods belonging to the computer vision field
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https://hal.univ-lorraine.fr/tel-01749418
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Ameni Boumaiza. Reconnaissance et localisation de symboles dans les documents graphiques : approches basées sur le treillis de concepts. Autre [cs.OH]. Université de Lorraine, 2013. Français. ⟨NNT : 2013LORR0028⟩. ⟨tel-01749418⟩

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