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International Journal of Computer Vision

, Volume 84, Issue 3, pp 308–324 | Cite as

Optimizing Gabor Filter Design for Texture Edge Detection and Classification

  • Roman Sandler
  • Michael Lindenbaum
Article

Abstract

An effective and efficient texture analysis method, based on a new criterion for designing Gabor filter sets, is proposed. The commonly used filter sets are 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 propose an algorithm for deriving the set of Gabor filters that maximizes the fraction of separable harmonic signal pairs in a given frequency range. The resulting filters differ significantly from the traditional ones. We test these maximal harmonic discrimination (MHD) filters in several texture analysis tasks: clustering, recognition, and edge detection. It turns out that the proposed filters perform much better than the traditional ones in these tasks. They can achieve performance similar to that of state-of-the-art, distribution based (texton) methods, while being simpler and more computationally efficient.

Keywords

Texture Gabor kernels Edge detection Classification 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Computer Science DepartmentTechnion, IITHaifaIsrael

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