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11ème IASTED International Conference on Computer Graphics and Imaging (CGIM), Innsbruck : Austria (2010)
PAVEMENT CRACKING DETECTION USING AN ANISOTROPY MEASUREMENT
Tien Sy Nguyen 1, Stéphane Begot 1, Florent Duculty 1, Jean-Christophe Bardet 1, Manuel Avila 1
(17/02/2010)

Automatic pavement cracking detection is a part of road maintenance and rehabilitation strategies. Cracks detection is one of the main features used by road authorities to manage efficiently its networks. Different systems are available to perform road analysis. We give a short description of some of them. Apparatus which was used to provide our images is described with more details. Road surface is made using randomly organized aggregates which can have different sizes. Scanned pictures of theses surfaces appear as random distribution of a reduced set of gray levels. Automatic crack detection is a difficult task due to the noisy pavement surface. In this paper, we introduce a measure of anisotropy for the characterization of cracks. The basic idea of this method is to detect the variation of features by considering different orientations. Noise variation and defect properties can be take into account by our method. Comparative results of anisotropy method with threshold method and 2D wavelet transform method are presented to illustrate benefits of anisotropy. We show that this method can be used to detect others types of defects, such as joints.
1 :  Laboratoire PRISME (PRISME)
Université d'Orléans : EA4229 – ENSI Bourges
Informatique/Traitement du signal et de l'image

Sciences de l'ingénieur/Traitement du signal et de l'image
crack detection – image analysis – road classification
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