Road Detection and Tracking from Aerial Desert Imagery Academic Article uri icon

abstract

  • We present a fast, robust road detection and tracking 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 clustering method is implemented to further extract the road. The proposed algorithm has been extensively tested on desert images obtained using an Unmanned Aerial Vehicle. Our results indicate that we are able to successfully and accurately detect roads in 96% of the images. We experimentally validated our algorithm on over a thousand aerial images obtained using our UAV. These images consist of straight and curved roads in various conditions with significant changes in lighting and intensity. We have also developed a road-tracking algorithm that searches a local rectangular area in successive images. Initial results are presented that shows the efficacy and the robustness of this algorithm. Using this road tracking algorithm we are able to further improve the road detection and achieve a 98% accuracy. 2011 Springer Science+Business Media B.V.

published proceedings

  • JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

author list (cited authors)

  • Lin, Y., & Saripalli, S.

citation count

  • 22

complete list of authors

  • Lin, Yucong||Saripalli, Srikanth

publication date

  • October 2012