Geometric pattern matching under Euclidean motion

Authors

L. Paul Chew, Cornell Ann S. Bowers College of Computing and Information Science
Michael T. Goodrich, Whiting School of Engineering
Daniel P. Huttenlochera, Ben-Gurion University of the Negev
Klara Kedem, Ben-Gurion University of the Negev
Jon M. Kleinberg, Ben-Gurion University of the Negev
Dina Kravets, Department of Computer Science

Document Type

Article

Publication Date

1-1-1997

Abstract

Given two planar sets A and B, we examine the problem of determining the smallest ε such that there is a Euclidean motion (rotation and translation) of A that brings each member of A within distance ε of some member of B. We establish upper bounds on the combinatorial complexity of this subproblem in model-based computer vision, when the sets A and B contain points, line segments, or (filled-in) polygons. We also show how to use our methods to substantially improve on existing algorithms for finding the minimum Hausdorff distance under Euclidean motion.

Identifier

0001532918 (Scopus)

Publication Title

Computational Geometry Theory and Applications

External Full Text Location

https://doi.org/10.1016/0925-7721(95)00047-X

ISSN

09257721

First Page

113

Last Page

124

Issue

1-2

Volume

7

Grant

N00014-89-J-1988

Fund Ref

Xerox

Recommended Citation

Chew, L. Paul; Goodrich, Michael T.; Huttenlochera, Daniel P.; Kedem, Klara; Kleinberg, Jon M.; and Kravets, Dina, "Geometric pattern matching under Euclidean motion" (1997). Faculty Publications. 16941.
https://digitalcommons.njit.edu/fac_pubs/16941