Share Email Print

Proceedings Paper

Identification and correction of road courses by merging successive segments and using improved attributes
Author(s): Dimitri Bulatov; Gisela Häufel; Melanie Pohl
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Both in military and civil applications, there is an urgent need for a highly up-to-date road data, which should be ideally semantically structured (into main roads, walking paths, escape ways, etc.) with application-driven attributes, such as road width, road type, surface condition and many others. A vectorization algorithm processing aerial images recently acquired yields an up-to-date road vector data, which are, however, often represented by wriggly, noisy polylines without semantics. The reasons for zigzagged street courses are insufficiencies in the intermediate results of sensor data processing (orthophotos, elevation maps) and occlusions caused by trees, buildings, and others. In the current contribution, an improved computation of geometric attributes will be explained which makes a difference between straight and circular (or elliptic) polylines. Using improved attributes, the candidates for polylines having identical course and sharing a junction are determined. From such candidates, we form chains of polylines. These chains correspond better to the intuitive perception of the term street than the previously used road polylines, because, even after being interrupted by narrower side roads, a chain maintains its label. The generalization of chains with simultaneously adjusting positions of junctions is evidently performed. We apply a generalization with the purpose-based modification of a well-known polyline simplification algorithm once chain-wise and once polyline-wise in order to show - by means of qualitative results - the advantages of the chain-wise generalization.

Paper Details

Date Published: 26 October 2016
PDF: 11 pages
Proc. SPIE 10008, Remote Sensing Technologies and Applications in Urban Environments, 100080V (26 October 2016); doi: 10.1117/12.2239208
Show Author Affiliations
Dimitri Bulatov, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Gisela Häufel, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Melanie Pohl, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)

Published in SPIE Proceedings Vol. 10008:
Remote Sensing Technologies and Applications in Urban Environments
Thilo Erbertseder; Thomas Esch; Nektarios Chrysoulakis, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?