Effective similarity measurement for key-point matching in images

Sungmin Lee, Seung Won Jung, Chee Sun Won

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Different similarity measures between the descriptors of the key-points certainly yield different performances in image matching. In this paper we introduce an effective similarity measurement, which considers the distances of each key-point in a query image and its matched key-point with the smallest distance in the test image. Therefore, the distances of all key-points in the query image to the corresponding matched key-points in the test image contribute to the final similarity measurement. On the other hand, the previous method considers only the distances less than a threshold value of all possible key-point pairs, which may ignore a significant part of the key-points in the query image. Our experiments show that the proposed measure yields better performance for image similarity matching and retrieval.

Original languageEnglish
Pages (from-to)223-228
Number of pages6
JournalLecture Notes in Electrical Engineering
Volume373
DOIs
StatePublished - 2015

Keywords

  • Image retrieval
  • Image similarity measure
  • Key-point detector/descriptor
  • SIFT

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