Maximizing the area of an axially symmetric polygon inscribed in a simple polygon

In this paper we solve the following optimization problem: given a simple polygon P, what is the maximum-area polygon that is axially symmetric and is contained in P? This problem pops up in shape reasoning when planar shapes are approximated by simpler shapes, e.g., symmetric shapes, or when they are decomposed hierarchically into simpler shapes. We propose an algorithm for solving the problem, analyze its running time, and describe our implementation of it (for the case of a convex polygon). The algorithm is based on building and investigating a planar map, each cell of which corresponds to a different configuration of the inscribed polygon. We prove that the complexity of the map is O(n^4), where n is the complexity of P. For a convex polygon the complexity is @Q(n^3) in the worst case. A substantial part of the work concentrates on calculation and analysis of arcs of the planar map. Arcs represent topological changes of the structure of the inscribed polygon, and are determined by the geometry of the original polygon. For each face of the map we calculate the area function of the inscribed polygons and look for a global maximum of the compound area function. We achieve this goal by using a numerical method.

[1]  Chan-Su Shin,et al.  Inscribing an axially symmetric polygon and other approximation algorithms for planar convex sets , 2006, Comput. Geom..

[2]  Jean-Paul Penot New methods in optimization and their industrial uses : state of the art, recent advances, perspectives : proceedings of the symposia held in Pau, October 19-29, 1987 and Paris, November 19, 1987 , 1989 .

[3]  R. VENKATASUBRAMANIAN On the Area of Intersection Between Two Closed 2-D Objects , 1995, Inf. Sci..

[4]  Joseph O'Rourke,et al.  Handbook of Discrete and Computational Geometry, Second Edition , 1997 .

[5]  Panos M. Pardalos,et al.  Quadratic programming with one negative eigenvalue is NP-hard , 1991, J. Glob. Optim..

[6]  Mark de Berg,et al.  Computing the Maximum Overlap of Two Convex Polygons under Translations , 1996, Theory of Computing Systems.

[7]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[8]  Eldon Hansen,et al.  Global optimization using interval analysis , 1992, Pure and applied mathematics.

[9]  J. Hiriart-Urruty,et al.  Comparison of public-domain software for black box global optimization , 2000 .

[10]  Micha Sharir,et al.  Davenport-Schinzel sequences and their geometric applications , 1995, Handbook of Computational Geometry.

[11]  Alexander H. G. Rinnooy Kan,et al.  A stochastic method for global optimization , 1982, Math. Program..

[12]  Bruce Randall Donald,et al.  On the Area Bisectors of a Polygon , 1999, Discret. Comput. Geom..

[13]  Henk J. A. M. Heijmans,et al.  Minkowski decomposition of convex polygons into their symmetric and asymmetric parts , 1998, Pattern Recognit. Lett..

[14]  Lester Ingber,et al.  Simulated annealing: Practice versus theory , 1993 .

[15]  Peter Gritzmann,et al.  On the complexity of some basic problems in computational convexity: I. Containment problems , 1994, Discret. Math..