Automatic road extraction from satellite imagery using LEGION networks

Authors:
Jiangye Yuan;DeLiang Wang;Bo Wu;Lin Yan;Rongxing Li
Affiliations:
Department of Computer Science & Engineering and Center for Cognitive Science, The Ohio State University, Columbus, OH;Department of Computer Science & Engineering and Center for Cognitive Science, The Ohio State University, Columbus, OH;Mapping and GIS Laboratory, Department of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, Columbus, OH;Mapping and GIS Laboratory, Department of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, Columbus, OH;Mapping and GIS Laboratory, Department of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, Columbus, OH
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

We present an automatic method for road extraction from satellite imagery. The core of the proposed method is Locally Excitatory Globally Inhibitory Oscillator Networks (LEGION). We decompose the road extraction task into three stages. The first stage is image segmentation by LEGION. In the second stage, we compute the medial axis of each segment and select the segments with narrow widths. The third is the road grouping stage. With the medial axes, alignment-dependent connections between medial axis points are established and LEGION is utilized to group the well-aligned medial axes, which represent extracted road segments. Due to the selective gating mechanism of LEGION, different roads in an image are grouped separately. Experimental results on synthetic and real images show the effectiveness of this method.