Automatic extraction of roads from aerial images based on scale-space and snakes

Ivan Laptev, Helmut Mayer, Tony Lindeberg, Wolfgang Eckstein, Carsten Steger, Albert Baumgartner

Technical report CVAP240, ISRN KTH NA/P--00/06--SE. Department of Numerical Analysis and Computing Science, KTH (Royal Institute of Technology), S-100 44 Stockholm, Sweden, March 2000.

Revised version in Machine Vision and Applications, 12(1):23-31, 2000.

Abstract

We propose a new approach for automatic road extraction from aerial imagery with a model and a strategy mainly based on the multi-scale detection of roads in combination with geometry-constrained edge extraction using snakes. A main advantage of our approach is, that it allows for the first time a bridging of shadows and partially occluded areas using the heavily disturbed evidence in the image. Additionally, it has only few parameters to be adjusted. The road network is constructed after extracting crossings with varying shape and topology. We show the feasibility of the approach not only by presenting reasonable results but also by evaluating them quantitatively based on ground truth.

Keywords: automatic road extraction, aerial imagery, snakes, multi-scale, evaluation

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Ivan Laptev <laptev@nada.kth.se>