Localisation et reconstruction du réseau routier par vectorisation d'image THR et approximation des contraintes de type "NURBS"

Abstract : The aim of this thesis is to establish a road network extraction system in urban areas from very high resolution satellite images. In this context, we proposed two approaches to locate roads. The first one is based on the process of converting the image into a vector form. The originality of this approach lies in the use of a geometric method to ensure the shift into a vector representation of the original image and the establishment of a logical formalism based on a set of perceptual criteria. It allows the filtering of unnecessary information and extracting linear structures. In the second approach, we proposed an algorithm based on the wavelet theory, it particularly highlights the two axis multi-resolution and multi-direction. Thus, we introduce a road localization approach, which manage the frequency multidirectional data resulting from the transform using the Log-Gabor wavelet. In the localization step, we presented two road detectors, which are capable of exploiting the radiometric, geometric and frequency data. However, this data cannot allow accurate and precise results. To overcome this drawback, a tracking algorithm is needed. We propose the reconstruction of road networks by NURBS curves. This approach is based on a landmark set of points identified in the localization phase and presents a new concept, noted by NURBSC. NURBSC is based on the geometrical constraints of shapes to be approximated. We connect road segments identified in order to obtain continuous road network.
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Mohamed Naouai. Localisation et reconstruction du réseau routier par vectorisation d'image THR et approximation des contraintes de type "NURBS". Mathématiques générales [math.GM]. Université de Strasbourg, 2013. Français. ⟨NNT : 2013STRAH015⟩. ⟨tel-00994333⟩

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