The Application of Mathematical Morphology and Pattern Recognition to Building Polygon Simplification

Abstract

The simplification of inhabited map area, especially simplifying the urban inhabited map area, is a difficult problem of automatic map generalization all along. There are many research results about this item in recent years, most of them are vector-based algorithms, and the others are raster-based. There is no perfect method which can make satisfactory generalization of inhabited map area yet. The main reason of this status is that it is difficult to get and use the semantic and spatial information of inhabited map area. In this paper, we present an approach to simplifying building polygon-one aspect of the simplification of inhabited map area, which is supported by a data model combining the raster and the vector model and adopt the methods of mathematical morphology and pattern recognition assisted by Neural Network. A system based on this method is carried out in the environment of Visual C~(++), the results of test prove that the method is in evidence on preserving the shape characters of urban blocks. This approach, integrating the knowledge of map generalization into the simplification of graph, is an attempt on intellectualizing automatic map generalization.

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