Color Cartographic Pattern Recognition Using the Coarse to Fine Scale Method

  • Efrén González-Gómez
  • Serguei Levachkine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)


Hard problem of cartographic pattern recognition in fine scale maps, using information that comes from coarse scale maps, is considered. The maps are raster-scanned color maps of different thematic, representing the same territory in coarse and fine scale respectively. A solution called Coarse-to-Fine Scale Method is proposed. This method is defined in terms of means: coarse scale maps and their information; concepts: image associated function, cartographic knowledge domain and cartographic pattern; and tools: a set of clustering criteria of the Logical Combinatorial Pattern Recognition.


  1. 1.
    Martínez-Trinidad, J.F., Guzmán-Arenas, A.: The Logical Combinatorial Approach to Pattern Recognition, an Overview through Selected Works. Pattern Recognition 34(1), 741–751 (2001)zbMATHCrossRefGoogle Scholar
  2. 2.
    Levachkine, S.: Raster to Vector Conversion of Color Cartographic Maps for Analytical GIS. In: Lladós, J., Kwon, Y.-B. (eds.) GREC 2003. LNCS, vol. 3088, pp. 77–91. Springer, Heidelberg (2003)Google Scholar
  3. 3.
    Martínez-Trinidad, J.F., Ruiz-Shulcloper, J.: Fuzzy Clustering of Semantic Spaces. Pattern Recognition 34(4), 783–793 (2001)zbMATHCrossRefGoogle Scholar
  4. 4.
    Levachkine, S. P., Polchkov, E.A.: Integrated Technique for Automated Digitization of Raster Maps. Revista Digital Universitaria 1(1) (2000), Available on-line at
  5. 5.
    Levachkine, S., Torres, M., Moreno, M., Quintero, R.: Simultaneous Segmentation-Recognition-Vectorization of Meaningful Geographical Objects in Geo-Images. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, pp. 635–642. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Angulo, J., Serra, J.: Mathematical Morphology in Color Spaces Applied to the Analysis of Cartographic Images. In: Levachkine, S., Serra, J., Egenhofer, M. (eds.) Semantic Processing of Spatial Data, Research on Computing Science, vol. 4, pp. 59–66 (2003)Google Scholar
  7. 7.
    Levachkine, S., Velázquez, A., Alexandrov, V., Kharinov, M.: Semantic Analysis and Recognition of Raster-scanned Color Cartographic Images. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, pp. 178–189. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Lazo-Cortés, M., Ruiz-Shulcloper, J., Alba-Cabrera, E.: An Overview of the Evolution of the Concept of Testor. Pattern Recognition 34(4), 753–762 (2001)zbMATHCrossRefGoogle Scholar
  9. 9.
    Torres-Ruiz, M., Levachkine, S.: Semantics Definition to Represent Spatial Data. In: Levachkine, S., et al. (eds.) Proc. International Workshop on Semantic Processing of Spatial Data (GEOPRO 2002), Mexico City, Mexico, December 3-4 (2002)Google Scholar
  10. 10.
    Meyers, G.K., Chen, C.-H.: Verification–based Approach for Automated Text and Feature Extraction from Raster-scanned Maps. In: Kasturi, R., Tombre, K. (eds.) Graphics Recognition 1995. LNCS, vol. 1072, pp. 190–203. Springer, Heidelberg (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Efrén González-Gómez
    • 1
  • Serguei Levachkine
    • 1
  1. 1.Centre for Computing Research (CIC) – National Polytechnic Institute (IPN)UPALMZ, CIC BuildingMexico CityMexico

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