Thin Nets Extraction Using a Multi-scale Approach

Thin nets are the lines where the grey level function is locally extremum in a given direction. Recently, we have shown that it is possible to characterize the thin nets using diierential properties of the image surface. However, the method failed when these structures present diierent widths. In this paper we show that, the extraction process of the thin nets, having diierent width, requires a multi-scale analysis of the image. To design the fusion process of the multi-scale information , we will study the behavior of the differential properties of the image surface, in particular the curvatures, in scale space. We illustrate the eeciency of the proposed multi-scale approach by extracting roads and blood vessels of diierent widths in satellite and medical images.