EVALUATING THE POTENTIAL OF CLUSTERING TECHNIQUES FOR 3D OBJECT EXTRACTION FROM LIDAR DATA

Farhad Samadzadegan, Mehdi Maboodi, Sara Saeedi, Ahmad Javaheri

Abstract

During the last decade airborne laser scanning (LIDAR) has become a mature technology which is now widely accepted for 3D data collection. Nevertheless, these systems have the disadvantage of not representing the desirable bare terrain, but the visible surface including vegetation and buildings. To generate high quality bare terrain using LIDAR data, the most important and difficult step is filtering, where non-terrain 3D objects such as buildings and trees are eliminated while keeping terrain points for quality digital terrain modelling. The main goal of this paper is to investigate and compare the potential of procedures for clustering of LIDAR data for 3D object extraction. The study aims at a comparison of K-Means clustering, SOM and Fuzzy C-Means clustering applied on range laser images. For evaluating the potential of each technique, the confusion matrix concept is employed and the accuracy evaluation is done qualitatively and quantitatively.

References

  1. Axelsson, P., 1999. Processing of laser scanner data - algorithms and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3): 138- 147.
  2. Cohen, J. 1960, "A coefficient of agreement for nominal scales", "Educational and Psychological Measurement", Vol. 20(1): pp. 37-46
  3. Davies, D.L. and Bouldin, D.W. (1979). "A Cluster Separation Measure." IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2), 224-227.
  4. Haala,N and Brenner, "Extraction of buildings and trees in urban environments", ISPRS Journal of Photogrammetry & Remote Sensing V 54(2-3), 130- 137 (1999).
  5. Halkidi, M., Batistakis, I.and Vazirgiannis, M. (2001). "On Clustering Validation Techniques", Journal of Intelligent Information Systems, 17:2/3, 107-145
  6. Hubert, L.J. Arabie, P., 1985, "Comparing partitions", Journal of Classification, Vol. 2, pp. 193-218.
  7. Kohonen, T., 1989, "Self-Organization and Associative Memory", Springer-Verlag.
  8. Maas, H.G., 1999. The potential of height texture measures for the segmentation of airborne laserscanner data.
  9. Mass, H. Vosselman, G. (2001), "Two algorithms for extracting building models from raw laser" OEEPE Workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Elevation Models, Stockholm, Official Publication OEEPE no.40,2001, 62-72
  10. Roggero, M., 2002. "Object segmentation with region growing and principal component analysis", International Archives of Photogrammetry and Remote Sensing, Vol. 34, Part 3A, Graz, Austria
  11. Rottensteiner, F., Briese, Ch., 2002. "A new method for building extraction in urban areas from high-resolution LIDAR data", International Archives of Photogrammetry and Remote Sensing, Vol. 34, Part 3A, Graz, Austria
  12. Sithole, George, Vosselman, George,2003, "Comparison of Filtering Algorithm"Proceedings of the Fourth International Airborne Remote Sensing Conference, Ottawa, Canada. pp. 154-161.
  13. TopScan, 2004. Airborne LIDAR Mapping Systems. http://www.topscan.de/en/luft/messsyst.html (accessed 10 Feb. 2004)
Download


Paper Citation


in Harvard Style

Samadzadegan F., Maboodi M., Saeedi S. and Javaheri A. (2006). EVALUATING THE POTENTIAL OF CLUSTERING TECHNIQUES FOR 3D OBJECT EXTRACTION FROM LIDAR DATA . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 149-154. DOI: 10.5220/0001378301490154


in Bibtex Style

@conference{visapp06,
author={Farhad Samadzadegan and Mehdi Maboodi and Sara Saeedi and Ahmad Javaheri},
title={EVALUATING THE POTENTIAL OF CLUSTERING TECHNIQUES FOR 3D OBJECT EXTRACTION FROM LIDAR DATA},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={149-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001378301490154},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - EVALUATING THE POTENTIAL OF CLUSTERING TECHNIQUES FOR 3D OBJECT EXTRACTION FROM LIDAR DATA
SN - 972-8865-40-6
AU - Samadzadegan F.
AU - Maboodi M.
AU - Saeedi S.
AU - Javaheri A.
PY - 2006
SP - 149
EP - 154
DO - 10.5220/0001378301490154