Approximate steerability of Gabor filters for feature detection

I. Kalliomäki*, J. Lampinen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


We discuss the connection between Gabor filters and steerable filters in pattern recognition. We derive optimal steering coefficients for Gabor filters and evaluate the accuracy of the approximative orientation steering numerically. Gabor filters can be well steerable, but the error of the approximation depends heavily on the parameters. We show how a rotation invariant feature similarity measure can be obtained using steerability.

Original languageEnglish
Title of host publicationIMAGE ANALYSIS
EditorsH. Kalviainen, J. Parkkinen, A. Kaarna
PublisherSpringer Berlin Heidelberg
Number of pages10
ISBN (Electronic)978-3-540-31566-7
ISBN (Print)978-3-540-26320-3
Publication statusPublished - 2005
MoE publication typeA3 Part of a book or another research book

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743

Fingerprint Dive into the research topics of 'Approximate steerability of Gabor filters for feature detection'. Together they form a unique fingerprint.

Cite this