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Extraction de structures fines sur des images texturées : application à la détection automatique de fissures sur des images de surface de chaussées

Abstract : These last decades have seen application of automatic inspection in many fields thanks to advanced vision sensors and image analysis methods. However, the difficult nature of pavement images, the small size of defects (cracks) lead to the fact that inspection in this area is done mostly manually. Each year in France, operator must view images of thousands kilometers of roads to detect these degradations. This method is expensive, slow and has a rather subjective result. The objective of this thesis is to develop a method for the detection and the classification of cracks on these pavement images automatically. In this thesis, a new method of segmentation has been developed: the Free Form Anisotropy (FFA). On one hand, this method allows to take into account both the features concerning form and intensity of cracks, for the detection. On the other hand, a new model is used to search minimum paths in graphs (images). This minimum path follows crack form when crack is present. After segmentation, extraction and classification of defects are performed by the Standard Hough Transform and by calculating local orientation of pixels. Experimental results have been obtained from different image databases and compared with other existing methods.
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Tien Sy Nguyen. Extraction de structures fines sur des images texturées : application à la détection automatique de fissures sur des images de surface de chaussées. Autre. Université d'Orléans, 2010. Français. ⟨NNT : 2010ORLE2048⟩. ⟨tel-00592482⟩

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