Sinuosity pattern recognition of road features for segmentation purposes in cartographic generalization

In line generalization, results depend very much on the characteristics of the line in question. For this reason it would be useful to obtain an automatic segmentation and enrichment of lines in order to apply to each section the best algorithm and the most appropriate parameter. In this paper, we present a line segmentation methodology based on a sinuosity pattern recognition measured by means of the effective-area as derived from the Visvalingam–Whyatt algorithm. Sections are determined by applying the Douglas–Peucker algorithm to a shape signature of the line: an effective-area/length space representation. An experiment is carried out with a set of 24 road features from a 1:25 000 scale map with a recommendation of the value of some parameters and a procedure for the automated search of that defined as natural number of sections. This procedure is based in the search of zones of stability in a graph of the number of sections when applying Douglas–Peucker to the shape signature. The results are positively assessed by an independent group of experts.