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Apports de nouveaux outils de traitement d'images et de programmation pour le relevé automatique de dégradations sur chaussées

Abstract : The road network is subject to degradations due to traffic and weather conditions. The detection of surface defects within pavement images is used to evaluate the road network and to schedule the necessary maintenance operations. The goal of this thesis is to develop unsupervised processing techniques for the analysis of 2D and 3D pavement images, which originate from imaging systems operating in the field of road engineering. We focus on the detection of road marking damage and the detection of cracks on the pavement. In the context of road marking, our objective is to realize an algorithm for detecting, recognizing, geo-locating and monitoring the wearing conditions of road marking using a panoramic imaging system. The performed image processing uses a color segmentation method to facilitate the extraction phase of the road marking zones. Then, an inverse perspective technique is applied to ease the identification of detected objects.The wearing conditions of road marking is established from the variations in the geometric (length, width, etc.) and colorimetric (white color level) characteristics of the objects identified in the image.In the context of road crack detection, our aspiration is the automatic segmentation of cracks within pavement images, assuming that they represent fine and dark features in the image. Among the many existing methods, our chosen approaches follow a classical scheme composed of three main phases, namely, a pre-processing phase to reduce the amount of information to be processed in the image, a processing phase to extract the points having a high likelihood of belonging to a crack on the road and a post-processing phase to estimate the severity and the damage level of the pavement. The performances of our proposed algorithms are evaluated on 2D and 3D real images, coming from 3 types of existing imaging devices for road engineering (VIAPIX®, LCMS and Aigle-RN).
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Submitted on : Wednesday, May 15, 2019 - 7:08:21 PM
Last modification on : Friday, December 4, 2020 - 3:30:32 AM


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  • HAL Id : tel-02130479, version 1



Wissam Kaddah. Apports de nouveaux outils de traitement d'images et de programmation pour le relevé automatique de dégradations sur chaussées. Traitement du signal et de l'image [eess.SP]. Université de Bretagne occidentale - Brest, 2018. Français. ⟨NNT : 2018BRES0102⟩. ⟨tel-02130479⟩



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