MPI-I-94-150
On characteristic points and approximate decision algorithms for the minimum Hausdorff distance
Chew, L. P. and Kedem, K. and Schirra, Stefan
September 1994, 10 pages.
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Status: available - back from printing
We investigate {\em approximate decision algorithms} for determining
whether the minimum Hausdorff distance between two points sets (or
between two sets of nonintersecting line segments) is at most
$\varepsilon$.\def\eg{(\varepsilon/\gamma)}
An approximate decision algorithm is a standard decision algorithm
that answers {\sc yes} or {\sc no} except when $\varepsilon$ is in
an {\em indecision interval}
where the algorithm is allowed to answer {\sc don't know}.
We present algorithms with indecision interval
$[\delta-\gamma,\delta+\gamma]$ where $\delta$ is the minimum
Hausdorff distance and $\gamma$ can be chosen by the user.
In other words, we can make our
algorithm as accurate as desired by choosing an appropriate $\gamma$.
For two sets of points (or two sets of nonintersecting lines) with
respective
cardinalities $m$ and $n$ our approximate decision algorithms run in
time $O(\eg^2(m+n)\log(mn))$ for Hausdorff distance under translation,
and in time $O(\eg^2mn\log(mn))$ for Hausdorff distance under
Euclidean motion.
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BibTeX
@TECHREPORT{ChewKedernSchirra94,
AUTHOR = {Chew, L. P. and Kedem, K. and Schirra, Stefan},
TITLE = {On characteristic points and approximate decision algorithms for the minimum Hausdorff distance},
TYPE = {Research Report},
INSTITUTION = {Max-Planck-Institut f{\"u}r Informatik},
ADDRESS = {Im Stadtwald, D-66123 Saarbr{\"u}cken, Germany},
NUMBER = {MPI-I-94-150},
MONTH = {September},
YEAR = {1994},
ISSN = {0946-011X},
}