Abstract
Over the past decades, considerable progress had been made in developing automatic image interpretation tools for remote sensing. There is, however, still a gap between the requirements of applications and system capabilities. Interpretation of noisy aerial images, especially in low resolution, is still difficult. We present a system aimed at detecting faint linear structures, such as pipelines and access roads, in aerial images. We introduce an orientation-weighted Hough transform for the detection of line segments and a Markov Random Field model for combining line segments into linear structures. Empirical results show that the proposed method yields good detection performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arulampalam, S., Maskell, S., Gordon, N.: A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing 50(2), 174–188 (2002)
Besag, J.: On the statistical analysis of dirty pictures. Journal of the Royal Statistical Society 48(2), 259–301 (1986)
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(11), 1222–1239 (2001)
Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)
Fua, P., Leclerc, Y.: Model driven edge detection. Machine Vision Application 3(2), 45–56 (1996)
Gao, R.: Detection of linear features in aerial images. Master’s thesis, University of Alberta (2009)
Gao, R., Bischof, W.F.: Bayesian tracking of linear structures in aerial images. In: Conference on Computer and Robot Vision (2009)
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing using Matlab. Pearson, Upper Saddle River (2004)
Illingworth, J., Kittler, J.: A survey of the Hough transform. Computer Vision, Graphics, and Image Processings 44(1), 87–116 (1998)
Manthalkar, R., Biswas, P., Chatterji, B.: Rotation invariant texture classification using even symmetric gabor filters. Pattern Recognition Letters 24, 2061–2068 (2003)
Barzohar, M., Cooper, D.: Automatic finding of main roads in aerial images using geometric-stochastic models and estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 707–721 (1996)
Merlet, N., Zerubia, J.: New prospects in line detection by dynamic programming. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(4), 426–431 (1996)
Ruwwe, C., Zölzer, U., Duprat, O.: Hough transform with weighting edge-maps. Visualization Imaging and Image Processing (2005)
Vosselman, G., Knecht, J.: Road tracing by profile matching and kalman filtering. In: Proc. Workshop Autom. Extraction Man-Made Objects From Aerial and Space Images, pp. 265–274 (1995)
Yedidia, J., Freeman, W., Weiss, Y.: Generalized belief propagation. In: Neural Information Processing Systems Conference, pp. 689–695 (2000)
Zhou, J., Bischof, W., Caelli, T.: Road tracking in aerial images based on human-computer interaction and Bayesian filtering. Photogrammetry and Remote Sensing 6(2), 108–124 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gao, R., Bischof, W.F. (2009). Detection of Linear Structures in Remote-Sensed Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_88
Download citation
DOI: https://doi.org/10.1007/978-3-642-02611-9_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02610-2
Online ISBN: 978-3-642-02611-9
eBook Packages: Computer ScienceComputer Science (R0)