Efficient Gabor filter design for texture segmentation

Thomas P. Weldon, William E. Higgins, Dennis F. Dunn

Research output: Contribution to journalArticlepeer-review

262 Scopus citations


Gabor filters have been successfully applied to a broad range of image processing tasks. The present paper considers the design of a single filter to segment a two-texture image. A new efficient algorithm for Gabor-filter design is presented, along with methods for estimating filter output statistics. The algorithm draws upon previous results that showed that the output of a Gabor-filtered texture is modeled well by a Rician distribution. A measure of the total output power is used to select the center frequency of the filter and is used to estimate the Rician statistics of the Gabor-filtered image. The method is further generalized to include the statistics of postfiltered outputs that are generated by a Gaussian filtering operation following the Gabor filter. The new method typically requires an order of magnitude less computation to design a filter than a previously proposed method. Experimental results demonstrate the efficacy of the method.

Original languageEnglish (US)
Pages (from-to)2005-2015
Number of pages11
JournalPattern Recognition
Issue number12
StatePublished - Dec 1996

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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