Optimal Gabor-filter design for texture segmentation

Authors:
Dennis F. Dunn;William E. Higgins
Affiliations:
Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park, PA;Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park, PA
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Year:
1993

Citing 3
Cited 0

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Texture Segmentation using 2-D Gabor Elementary Functions

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Abstract

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.