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Books > Computing & IT > Applications of computing > Image processing
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Mapping and Spatial Modelling for Navigation (Paperback, Softcover reprint of the original 1st ed. 1990)
Loot Price: R3,058
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Mapping and Spatial Modelling for Navigation (Paperback, Softcover reprint of the original 1st ed. 1990)
Series: NATO ASI Subseries F:, 65
Expected to ship within 10 - 15 working days
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The successful implementation of applications in spatial reasoning
requires paying attention to the representation of spatial data. In
particular, an integrated and uniform treatment of different
spatial features is necessary in order to enable the reasoning to
proceed quickly. Currently, the most prevalent features are points,
rectangles, lines, regions, surfaces, and volumes. As an example of
a reasoning task consider a query of the form "find all cities with
population in excess of 5,000 in wheat growing regions within 10
miles of the Mississippi River. " Note that this query is quite
complex. It requires- processing a line map (for the river),
creating a corridor or buffer (to find the area within 10 miles of
the river), a region map (for the wheat), and a point map (for the
cities). Spatial reasoning is eased by spatially sorting the data
(i. e. , a spatial index). In this paper we show how hierarchical
data structures can be used to facilitate this process. They are
based on the principle of recursive decomposition (similar to
divide and conquer methods). In essence, they are used primarily as
devices to sort data of more than one dimension and different
spatial types. The term quadtree is often used to describe this
class of data structures. In this paper, we focus on recent
developments in the use of quadtree methods. We concentrate
primarily on region data. For a more extensive treatment of this
subject, see [SameS4a, SameSSa, SameSSb, SameSSc, SameSga,
SameSgbj.
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