Pattern matching by sequential subdivision of transformation space

Mingtian Ni, Stephen E. Reichenbach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Pattern matching is a well-known pattern recognition technique. This paper proposes a novel pattern matching algorithm that searches transformation space by sequential subdivision. The algorithm subdivides the transformation space in depth-first manner by conducting boolean operations on the constraint sets that are defined by pairs of template points and target points. For constrained polynomial transformations that have no more than two parameters on each coordinate, a constraint set can be represented as a 2D polygon or a Cartesian product of 2D polygons. Then, the boolean operations can be computed through generic polygon clipping algorithms. Preliminary experiments on randomly generated point patterns show that the algorithm is effective and efficient under practical conditions.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages145-148
Number of pages4
DOIs
StatePublished - 2004
Externally publishedYes
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Conference

ConferenceProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period8/23/048/26/04

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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