Gabor Filter Analysis for Texture Segmentation

Gabor features are a common choice for texture analysis. The particular set of Gabor filters used for extracting the features is usually designed for optimal signal representation. We propose here an alternative criterion for designing the filter set. We consider a set of filters and its response to...

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Bibliographic Details
Main Authors: Sandler, R., Lindenbaum, M.
Format: Conference Proceeding
Language:English
Subjects:
Computer science
Distortion measurement
Feature extraction
Gabor filters
Harmonic analysis
Image segmentation
Power harmonic filters
Signal analysis
Signal design
Stability
Online Access:Request full text
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Description
Summary:Gabor features are a common choice for texture analysis. The particular set of Gabor filters used for extracting the features is usually designed for optimal signal representation. We propose here an alternative criterion for designing the filter set. We consider a set of filters and its response to pairs of harmonic signals. Two signals are considered separable if the corresponding two sets of vector responses are disjoint in at least one of the components. We look for the set of Gabor filters that maximizes the fraction of separable harmonic signal pairs. The resulting filters are significantly different from the traditional ones. We test these maximal harmonic discrimination (MHD) filters using two texture discrimination methods, and describe their advantages over traditional filters.
ISSN:2160-7508
2160-7516
DOI:10.1109/CVPRW.2006.86