Geometric pattern matching under Euclidean motion

L. Paul Chew, Michael T. Goodrich, Daniel P. Huttenlochera, Klara Kedem, Jon M. Kleinberg, Dina Kravets

Research output: Contribution to journalArticlepeer-review

81 Scopus citations


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.

Original languageEnglish
Pages (from-to)113-124
Number of pages12
JournalComputational Geometry: Theory and Applications
Issue number1-2
StatePublished - 1 Jan 1997

ASJC Scopus subject areas

  • Computer Science Applications
  • Geometry and Topology
  • Control and Optimization
  • Computational Theory and Mathematics
  • Computational Mathematics


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