Developing an automated vectorizing system as an input method for a geographic information system (GIS) is of extreme importance due to the fact that an input process takes a lot of time and cost in constructing a GIS. Most vectorizing systems require users to set the parameters as appropriately as possible for a particular map image, but it is quite difficult for a novice to adjust the parameters appropriately. This paper proposes a knowledge-based system for automated vectorization, allowing an appropriate choice of the parameters. Since thinning of the input image to produce a skeleton of unit width is a prerequisite for the automated vectorization among several steps, the performance of representative thinning algorithms is systematically evaluated in various map images, and appropriate rules for the maps are devised. Each rule in the knowledge base is characterized by the type of map, and by the resolution, line width, slope and protrusions. Experimental results with various map images show that the proposed system is superior in terms of performance and convenience of use.
|Number of pages||14|
|Journal||Engineering Applications of Artificial Intelligence|
|Publication status||Published - 2000 Apr 1|
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering