Hausdorff-distance enhanced matching of scale invariant feature transform descriptors in context of image querying

J.I. Olszewska, D. Wilson

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

11 Citations (Scopus)

Abstract

Reliable and effective matching of visual descriptors is a key step for many vision applications, e.g. image retrieval. In this paper, we propose to integrate the Hausdorff distance matching together with our pairing algorithm, in order to obtain a robust while computationally efficient process of matching feature descriptors for image-to-image querying in standards datasets. For this purpose, Scale Invariant Feature Transform (SIFT) descriptors have been matched using our presented algorithm, followed by the computation of our related similarity measure. This approach has shown excellent performance in both retrieval accuracy and speed.
Original languageEnglish
Title of host publication2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES)
PublisherIEEE
Pages91-96
Number of pages6
ISBN (Electronic)9781467326957
ISBN (Print)9781467326940
DOIs
Publication statusPublished - 30 Jul 2012
Externally publishedYes

Publication series

NameIEEE Conference Proceedings
PublisherIEEE
ISSN (Print)1543-9259

Keywords

  • image retrieval
  • conferences
  • robustness
  • feature extraction
  • pattern recognition
  • computer vision

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