Optimal Gabor-filter design for texture segmentation

Dennis F. Dunn, William Evan Higgins

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

18 Scopus citations


Many proposed texture-segmentation schemes are based on a filter-bank model. The filters, henceforth referred to as Gabor filters, have typically been designed empirically. Dunn et al. have recently derived analytical criteria for designing appropriate Gabor filters; they did not discuss how to design filters for general natural textures. This paper presents an algorithm for designing optimal Gabor filters. The algorithm assumes that an image contains two different textures and that prototype samples of the desired textures are given. It uses a decision-theoretic framework, based on modeling a Gabor-filter output as a Rician distribution, for designing optimal filters. To gain more robust results, we also propose a multiple-filter segmentation scheme. Experimental results verify the efficacy of our methods.

Original languageEnglish (US)
Title of host publicationImage and Multidimensional Signal Processing
PublisherPubl by IEEE
ISBN (Print)0780309464
StatePublished - Jan 1 1993
EventIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) - Minneapolis, MN, USA
Duration: Apr 27 1993Apr 30 1993


OtherIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5)
CityMinneapolis, MN, USA

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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