Noise tolerant object recognition using Gabor filtering

Joni Kristian Kamarainen, Ville Kyrki, Heikki Kälviäinen

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

16 Citations (Scopus)

Abstract

The choice of features for invariant object recognition is one of the most essential problems in computer vision. The authors have recently proposed Gabor filtering based feature extraction methods which have been successfully applied in invariant object recognition. In this study, the Gabor filtering based feature extraction is further analysed in terms of distortion tolerance which is an essential property for many applications. Experiments indicate that an accurate recognition can be achieved in the presence of significant amounts of distortions.

Original languageEnglish
Title of host publicationInternational Conference on Digital Signal Processing, DSP
PublisherIEEE
Pages1349-1352
Number of pages4
Volume2
ISBN (Print)0780375033
DOIs
Publication statusPublished - 2002
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Digital Signal Processing - Santorini, Greece
Duration: 1 Jul 20023 Jul 2002
Conference number: 14

Conference

ConferenceInternational Conference on Digital Signal Processing
Abbreviated titleDSP
CountryGreece
CitySantorini
Period01/07/200203/07/2002

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