3,559 research outputs found
Computation of the Hausdorff distance between sets of line segments in parallel
We show that the Hausdorff distance for two sets of non-intersecting line
segments can be computed in parallel in time using O(n)
processors in a CREW-PRAM computation model. We discuss how some parts of the
sequential algorithm can be performed in parallel using previously known
parallel algorithms; and identify the so-far unsolved part of the problem for
the parallel computation, which is the following: Given two sets of
-monotone curve segments, red and blue, for each red segment find its
extremal intersection points with the blue set, i.e. points with the minimal
and maximal -coordinate. Each segment set is assumed to be intersection
free. For this intersection problem we describe a parallel algorithm which
completes the Hausdorff distance computation within the stated time and
processor bounds
Pattern Matching for sets of segments
In this paper we present algorithms for a number of problems in geometric
pattern matching where the input consist of a collections of segments in the
plane. Our work consists of two main parts. In the first, we address problems
and measures that relate to collections of orthogonal line segments in the
plane. Such collections arise naturally from problems in mapping buildings and
robot exploration.
We propose a new measure of segment similarity called a \emph{coverage
measure}, and present efficient algorithms for maximising this measure between
sets of axis-parallel segments under translations. Our algorithms run in time
O(n^3\polylog n) in the general case, and run in time O(n^2\polylog n) for
the case when all segments are horizontal. In addition, we show that when
restricted to translations that are only vertical, the Hausdorff distance
between two sets of horizontal segments can be computed in time roughly
O(n^{3/2}{\sl polylog}n). These algorithms form significant improvements over
the general algorithm of Chew et al. that takes time . In the
second part of this paper we address the problem of matching polygonal chains.
We study the well known \Frd, and present the first algorithm for computing the
\Frd under general translations. Our methods also yield algorithms for
computing a generalization of the \Fr distance, and we also present a simple
approximation algorithm for the \Frd that runs in time O(n^2\polylog n).Comment: To appear in the 12 ACM Symposium on Discrete Algorithms, Jan 200
On the computation of zone and double zone diagrams
Classical objects in computational geometry are defined by explicit
relations. Several years ago the pioneering works of T. Asano, J. Matousek and
T. Tokuyama introduced "implicit computational geometry", in which the
geometric objects are defined by implicit relations involving sets. An
important member in this family is called "a zone diagram". The implicit nature
of zone diagrams implies, as already observed in the original works, that their
computation is a challenging task. In a continuous setting this task has been
addressed (briefly) only by these authors in the Euclidean plane with point
sites. We discuss the possibility to compute zone diagrams in a wide class of
spaces and also shed new light on their computation in the original setting.
The class of spaces, which is introduced here, includes, in particular,
Euclidean spheres and finite dimensional strictly convex normed spaces. Sites
of a general form are allowed and it is shown that a generalization of the
iterative method suggested by Asano, Matousek and Tokuyama converges to a
double zone diagram, another implicit geometric object whose existence is known
in general. Occasionally a zone diagram can be obtained from this procedure.
The actual (approximate) computation of the iterations is based on a simple
algorithm which enables the approximate computation of Voronoi diagrams in a
general setting. Our analysis also yields a few byproducts of independent
interest, such as certain topological properties of Voronoi cells (e.g., that
in the considered setting their boundaries cannot be "fat").Comment: Very slight improvements (mainly correction of a few typos); add DOI;
Ref [51] points to a freely available computer application which implements
the algorithms; to appear in Discrete & Computational Geometry (available
online
Approximations of the Wiener sausage and its curvature measures
A parallel neighborhood of a path of a Brownian motion is sometimes called
the Wiener sausage. We consider almost sure approximations of this random set
by a sequence of random polyconvex sets and show that the convergence of the
corresponding mean curvature measures holds under certain conditions in two and
three dimensions. Based on these convergence results, the mean curvature
measures of the Wiener sausage are calculated numerically by Monte Carlo
simulations in two dimensions. The corresponding approximation formulae are
given.Comment: Published in at http://dx.doi.org/10.1214/09-AAP596 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Farthest-Polygon Voronoi Diagrams
Given a family of k disjoint connected polygonal sites in general position
and of total complexity n, we consider the farthest-site Voronoi diagram of
these sites, where the distance to a site is the distance to a closest point on
it. We show that the complexity of this diagram is O(n), and give an O(n log^3
n) time algorithm to compute it. We also prove a number of structural
properties of this diagram. In particular, a Voronoi region may consist of k-1
connected components, but if one component is bounded, then it is equal to the
entire region
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