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Computational Geometry
Volume 32, Issue 2, October 2005, Pages 139-158
 
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doi:10.1016/j.comgeo.2005.02.002    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2005 Elsevier B.V. All rights reserved.

Hausdorff approximation of convex polygons

Mario A. Lopeza, Corresponding Author Contact Information, 1, E-mail The Corresponding Author and Shlomo Reisnerb, 2, E-mail The Corresponding Author

aDepartment of Computer Science, University of Denver, Denver, CO 80208, USA bDepartment of Mathematics, University of Haifa, Haifa 31905, Israel

Received 29 February 2004; 
accepted 24 February 2005. 
Communicated by F. Hurtado. 
Available online 31 May 2005.

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Abstract

We develop algorithms for the approximation of convex polygons with n vertices by convex polygons with fewer (k) vertices. The approximating polygons either contain or are contained in the approximated ones. The distance function between convex bodies which we use to measure the quality of the approximation is the Hausdorff metric. We consider two types of problems: min-#, where the goal is to minimize the number of vertices of the output polygon, for a given distance var epsilon, and min-var epsilon, where the goal is to minimize the error, for a given maximum number of vertices. For min-# problems, our algorithms are guaranteed to be within one vertex of the optimal, and run in O(nlogn) and O(n) time, for inner and outer approximations, respectively. For min-var epsilon problems, the error achieved is within an arbitrary factor α>1 from the best possible one, and our inner and outer approximation algorithms run in O(f(α,P)dot operatornlogn) and O(f(α,P)dot operatorn) time, respectively. Where the factor f(α,P) has reciprocal logarithmic growth as α decreases to 1, this factor depends on the shape of the approximated polygon P.

Keywords: Convex polygons; Approximation algorithms; Hausdorff distance


Computational Geometry
Volume 32, Issue 2, October 2005, Pages 139-158
 
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