Fundamental frequency Gabor filters for object recognition

Joni Kamarainen*, Ville Kyrki, Heikki Kälviäinen

*Corresponding author for this work

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

29 Citations (Scopus)

Abstract

Gabor filters are a widely used feature extraction method in image analysis. In this study, a new method is presented that utilises Gabor filters for extracting fundamental frequencies of objects. The fundamental frequencies represent the shape of an object and can be used to classify objects with dissimilar spatial dimensions. Theoretical results are verified by experiments with real images of electronic components. Experiments indicate that the fundamental frequency Gabor filters are a robust tool for rotation and translation invariant object recognition.

Original languageEnglish
Title of host publicationInternational Conference on Pattern Recognition
PublisherIEEE
Pages628-631
Number of pages4
Volume16
DOIs
Publication statusPublished - 2002
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Pattern Recognition -
Duration: 11 Aug 200215 Aug 2002
Conference number: 16

Publication series

NameInternational Conference on Pattern Recognition
PublisherI E E E Computer Society; Institute of Electrical and Electronics Engineers
ISSN (Print)1051-4651

Conference

ConferenceInternational Conference on Pattern Recognition
Abbreviated title ICPR
Period11/08/200215/08/2002

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