Elastic graph matching on gabor feature representation at low image resolution

Yasuomi Sato, Yasutaka Kuriya

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

Abstract

We progressively improve conventional elastic graph matching (EGM) algorithm. In the conventional EGM, each node of a model graph can difficultly detect its corresponding precise position for the most similar Gabor feature extraction on an input low-resolution image. Solving this problem and then finding such a position, we propose a method that the node is allowed to fit among pixels by interpolating aliased Gabor feature representation between the pixels, which is calculated with the others extracted at the neighbor pixels. The model graph can thereby move to the most likely and more precise positions on the input low-resolution image.

Original languageEnglish
Title of host publicationArtificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
Pages387-394
Number of pages8
EditionPART 1
DOIs
Publication statusPublished - 2012 Oct 25
Event22nd International Conference on Artificial Neural Networks, ICANN 2012 - Lausanne, Switzerland
Duration: 2012 Sep 112012 Sep 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7552 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other22nd International Conference on Artificial Neural Networks, ICANN 2012
CountrySwitzerland
CityLausanne
Period12/9/1112/9/14

Keywords

  • Elastic Graph Matching
  • Interpolation for Aliased Gabor Feature Representation
  • Low Resolution Images

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Elastic graph matching on gabor feature representation at low image resolution'. Together they form a unique fingerprint.

  • Cite this

    Sato, Y., & Kuriya, Y. (2012). Elastic graph matching on gabor feature representation at low image resolution. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings (PART 1 ed., pp. 387-394). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7552 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-33269-2_49