ICRA 2012 Paper Abstract


Paper WeD110.5

Lin, Yucong (Arizona State University), Saripalli, Srikanth (Arizona State University)

Road Detection from Aerial Imagery

Scheduled for presentation during the Interactive Session "Interactive Session WeD-1" (WeD110), Wednesday, May 16, 2012, 16:30−17:00, Ballroom D

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 20, 2018

Keywords Aerial Robotics, Surveillance Systems, Visual Navigation


We present a fast, robust road detection algorithm for aerial images taken from an Unmanned Aerial Vehicle. A histogram-based adaptive threshold algorithm is used to detect possible road regions in an image. A probabilistic hough transform based line segment detection combined with a clus- tering method is implemented to further extract the road. The proposed algorithm has been extensively tested on desert and urban images obtained using an Unmanned Aerial Vehicle. Our results indicate that we are able to successfully and accurately detect roads in 97% of the images. We experimentally validated our algorithm on over ten thousand (10,000) aerial images obtained using our UAV. These images consist of intersecting roads, bifurcating roads and roundabouts in various conditions with significant changes in lighting and intensity. Our algorithm is able to successfully detect single roads effectively in almost all the images. It is also able to detect at least one road in over 95% of the images containing bifurcating or intersecting roads



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