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Knowledge-based segmentation for automatic map interpretation

  • Jurgen den Hartog
  • Ton ten Kate
  • Jan Gerbrands
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1072)

Abstract

In this paper, a knowledge-based framework for the top-down interpretation and segmentation of maps is presented. The interpretation is based on a priori knowledge about map objects, their mutual spatial relationships and potential segmentation problems. To reduce computational costs, a global segmentation is used when possible, but an applicable top-down segmentation strategy is chosen when errors in the global segmentation are detected. The interpretation system has been tested on utility maps and the experiments show that when a top-down resegmentation strategy is used to correct errors in the global segmentation, the recognition performance is improved significantly.

Keywords

Recognition Performance Search Area Object Type Search Action Initial Segmentation 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Jurgen den Hartog
    • 1
  • Ton ten Kate
    • 1
  • Jan Gerbrands
    • 2
  1. 1.TNO Institute of Applied PhysicsAD DelftThe Netherlands
  2. 2.Fac. of Electrical EngineeringDelft University of TechnologyGA DelftThe Netherlands

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