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Classification multi-modèles des images dans les bases Hétérogènes

Abstract : Image recognition is widely studied by the scientific community. The proposed research in this field is addressed to various applications of computer vision systems and multiple source image categorization. This PhD dissertation deals particularly with content based image recognition systems in heterogeneous databases. Images in this kind of databases belong to different concepts and represent a heterogeneous content. In this case and to ensure a reliable representation, a broad description is often required. However, the extracted features are not necessarily always suitable for the considered image database. Hence, the need of selecting relevant features based on the content of each database. In this work, an adaptive selection method is proposed. It considers only the most adapted features according to the used image database content. Moreover, selected features do not have generally the same performance degrees. Consequently, a specific classification algorithm which considers the discrimination powers of the different selected features is strongly recommended. In this context, the multiple kernel learning approach is studied and an improved kernel weighting method is presented. It proved that this approach is unable to describe the nonlinear relationships of different description kinds. Thus, we propose a new hierarchical multi-model classification method able to ensure a more flexible combination of multiple features. Experimental results confirm the effectiveness and the robustness of this new classification approach. In addition, the proposed method is very competitive in comparison with a set of approaches cited in the recent literature.
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https://tel.archives-ouvertes.fr/tel-00526649
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Submitted on : Friday, October 15, 2010 - 12:11:01 PM
Last modification on : Tuesday, June 30, 2020 - 11:56:08 AM
Long-term archiving on: : Sunday, January 16, 2011 - 2:49:13 AM

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  • HAL Id : tel-00526649, version 1

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Rostom Kachouri. Classification multi-modèles des images dans les bases Hétérogènes. Traitement du signal et de l'image [eess.SP]. Université d'Evry-Val d'Essonne, 2010. Français. ⟨tel-00526649⟩

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