Efficient image matching using concentric sampling features and boosting process

Pin Wu*, Jun-Wei Hsieh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents a novel template matching method to efficiently match and search image patterns. The method using concentric sampling structures, boosting process, and coarse-to-fine framework, differs from the traditional pattern matching schemes of time-exhausting correlation. The time complexity at searching stage is invariant to the dimension of concerned patterns. The rotation-invariant collection of concentric sub-samples represents as a reliable relaxation process of weak beliefs to efficiently reject the impossible location candidates. The concentric sampling approximation of integral images and the hierarchical scheme enable sifting out the patterns to process with the reduced complexity. Experimental result demonstrates the real-time performance on efficient pattern detection and geometry parameter estimation and the flexibility (on translation-, scaling-, and rotation-variant patterns) for various image analysis applications.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages2004-2007
Number of pages4
DOIs
StatePublished - 1 Dec 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: 12 Oct 200815 Oct 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2008 IEEE International Conference on Image Processing, ICIP 2008
CountryUnited States
CitySan Diego, CA
Period12/10/0815/10/08

Keywords

  • Boosting
  • Feature extraction
  • Integral feature
  • Pattern matching
  • Template matching

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