A Differential Approach for Fissures Detection on Road Surface Images

The present work is part of a more general study concerning the characterisation of road surface from images. Here, we deal with the search for some particular deteriorations, the surface's fissures. The encountered difficulties come from the nature of these images. On one hand, we have a grey levels distribution which is quite perfectly gaussian. On the other hand, the road's texture induces possible confusions between fissures and usual stone's separation. Most authors involved with the general problem of crack's detection base their researches on the following principle : a crack may be considered like a break of a given model. Our approach is absolutely different in that we don't directly use any homogeneity's hypothesis concerning the cracked object. In this paper, we present how some pure differential observations about the image surface introduce an original fissures detection process. We use a new and dedicated PDE's scheme to generate an appropriated scale- space from which it's rather easy to extract fissures edges. Finally, we show some results from real roads images.