Advertisement

Pattern Recognition in Road Networks on the Example of Circular Road Detection

  • Frauke Heinzle
  • Karl-Heinrich Anders
  • Monika Sester
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4197)

Abstract

The paper will introduce into the subject of recognition of typical patterns in road networks. Especially we will describe the search for ring structures and its implementation in detail. Applications to detect these patterns and to use them for eliciting additional implicit knowledge in vector data are shown. We will familiarise the reader with different methods and approaches for the automatic detection of those patterns in vector data. The retrieval of implicit information in vector data can be very helpful for many tasks, ranging from generalisation of maps to the spatial analysis and enrichment of GIS data to make it searchable by search engines.

Keywords

Road Network Vector Data Ring Road Implicit Information Geometric Moment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aloupis, G.: Geometric Measures of Data Depth. DIMACS Series in Discrete Mathematics and Theoretical Computer Science (accepted, December 2005)Google Scholar
  2. 2.
    Anders, K.H.: Level of Detail Generation of 3D Building Groups by Aggregation and Typification. In: Proceedings of 22nd International Cartographic Conference, July 9-16, 2005, La Coruña/Spain (2005)Google Scholar
  3. 3.
    Haralick, R.M., Shapiro, L.G.: Computer and Robot Vision, vol. I & II. Addison-Wesley, Reading (1992)Google Scholar
  4. 4.
    Heinzle, F., Sester, M., Anders, K.H.: Graph-based Approach for Recognition of Patterns and Implicit Information in Road Networks. In: Proceedings of 22nd International Cartographic Conference, La Coruña/Spain, July 9-16 (2005)Google Scholar
  5. 5.
    Jiang, B., Claramunt, C.: A Structural Approach to the Model Generalization of an Urban Street Network. GeoInformatica 8(2), 157–171 (2004)CrossRefGoogle Scholar
  6. 6.
    Jones, C.B., et al.: Spatial Information Retrieval and Geographical Ontologies: An Overview of the SPIRIT project. In: Proc. of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, pp. 387–388 (2002)Google Scholar
  7. 7.
    Koperski, K., Han, J.: Discovery of Spatial Association Rules in Geographic Information Databases. In: Egenhofer, M.J., Herring, J.R. (eds.) SSD 1995. LNCS, vol. 951, pp. 47–66. Springer, Heidelberg (1995)Google Scholar
  8. 8.
    Lu, W., Han, J., Ooi, B.C.: Discovery of General Knowledge in Large Spatial Databases. In: Proc. Far East Workshop on Geographic Information Systems, Singapore, pp. 275–289 (1993)Google Scholar
  9. 9.
    Mackaness, W., Edwards, G.: The Importance of Modelling Pattern and Structure in Automated Map Generalisation. In: Joint Workshop on Multi-Scale Representations of Spatial Data, Ottawa, Canada (2002)Google Scholar
  10. 10.
    Marshall, S.: Streets & Patterns. Spon Press, Taylor & Francis Group, New York (2005)Google Scholar
  11. 11.
    SPIRIT– Spatially-Aware Information Retrieval on the Internet (2005), http://www.geo-spirit.org/
  12. 12.
    Thomson, R., Richardson, D.: The ‘good continuation’ principle of perceptual organization applied to the generalization of road networks. In: Proceedings of the 19th International Cartographic Conference, Ottawa, pp. 1215–1223 (1999)Google Scholar
  13. 13.
    Tukey, J.: Mathematics and the picturing of data. In: Proceedings of the International Congress of Mathematicians, Vancouver, pp. 523–531 (1975)Google Scholar
  14. 14.
    Volz, S.: Data-Driven Matching of Geospatial Schemas. In: Cohn, A.G., Mark, D.M. (eds.) COSIT 2005. LNCS, vol. 3693, pp. 115–132. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  15. 15.
    Voss, K., Süße, H.: Adaptive Modelle und Invarianten für zweidimensionale Bilder. Shaker Verlag, Aachen (1995)Google Scholar
  16. 16.
    Witten, I.H., Frank, E.: Data Mining, Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers, San Francisco (2000)Google Scholar
  17. 17.
    Zhang, Q.: Modeling Structure and Patterns in Road Network Generalization. In: ICA Workshop on Generalisation and Multiple Representation, Leicester, UK (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Frauke Heinzle
    • 1
  • Karl-Heinrich Anders
    • 1
  • Monika Sester
    • 1
  1. 1.Institute of Cartography and GeoinformaticsUniversity of HannoverHannoverGermany

Personalised recommendations