Road Crack Extraction with Adapted Filtering and Markov Model-based Segmentation - Introduction and Validation

The automatic detection of road cracks is important in a lot of countries to quantify the quality of road surfaces and to determine the national roads that have to be improved. Many methods have been proposed to automatically detect the defects of road surface and, in particular, cracks: with tools of mathematical morphology, neuron networks or multiscale filter. These last methods are the most appropriate ones and our work concerns the validation of a wavelet decomposition which is used as the initialisation of a segmentation based on Markovian modelling. Nowadays, there is no tool to compare and to evaluate precisely the peformances and the advantages of all the existing methods and to qualify the efficiency of a method compared to the state of the art. In consequence, the aim of this work is to validate our method and to describe how to set the parameters.