Title
Gabor Filter Analysis for Texture Segmentation
Abstract
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.
Year
DOI
Venue
2006
10.1109/CVPRW.2006.86
CVPR Workshops
Field
DocType
ISBN
Computer vision,Signal processing,Disjoint sets,Pattern recognition,Computer science,Gabor wavelet,Harmonic,Image segmentation,Gabor filter,Harmonic analysis,Artificial intelligence,Gabor transform
Conference
0-7695-2646-2
Citations 
PageRank 
References 
8
0.62
20
Authors
2
Name
Order
Citations
PageRank
Roman Sandler11054.60
michael lindenbaum21578142.15