Modeling and computing ternary projective relations between regions

A Model for Ternary Projective Relations between Regions

Current spatial database systems offer limited querying capabilities beyond topological relations. This paper introduces a model for projective relations between regions to support other qualitative spatial queries. The relations are ternary because they are based on the collinearity invariant of three points under projective geometry. The model is built on a partition of the plane in five regi...

Relations between Interval Computing and Soft Computing

This volume is about knowledge processing with interval and soft computing, i.e., about techniques that use both interval and soft computing to process knowledge and about the results of applying these techniques. To better understand these techniques, in Chapter 1, we described fundamentals of interval computing, and in Chapter 2, we described the fundamentals of soft computing. Now it is time...

Topological Relations between Convex Regions

Topological relations between spatial objects are the most important kind of qualitative spatial information. Dozens of relation models have been proposed in the past two decades. These models usually make a small number of distinctions and therefore can only cope with spatial information at a fixed granularity of spatial knowledge. In this paper, we propose a topological relation model in whic...

Topological Relations between Discrete Regions

Topological reasoning is important for speeding up spatial queries, e.g. in GIS or in AI (robotics). While topological relations between spatial objects in the vector model (I R 2) are investigated thoroughly, we run into inconsistencies in the raster model (Z Z 2). But instead of reducing our requirements in case of reasoning in raster images we change from simple raster to a cellular decompos...

Spatial relations between indeterminate regions