Multi-phase texture segmentation using gabor features histograms based on wasserstein distance

Motong Qiao*, Wei Wang, Kwok Po NG

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We present a multi-phase image segmentation method based on the histogram of the Gabor feature space, which consists of a set of Gabor-filter responses with various orientations, scales and frequencies. Our model replaces the error function term in the original fuzzy region competition model with squared 2-Wasserstein distance function, which is a metric to measure the distance of two histograms. The energy functional is minimized by alternative minimization method and the existence of closed-form solutions is guaranteed when the exponent of the fuzzy membership term being 1 or 2. We test our model on both simple synthetic texture images and complex natural images with two or more phases. Experimental results are shown and compared to other recent results.

Original languageEnglish
Pages (from-to)1480-1500
Number of pages21
JournalCommunications in Computational Physics
Volume15
Issue number5
DOIs
Publication statusPublished - May 2014

Scopus Subject Areas

  • Physics and Astronomy (miscellaneous)

User-Defined Keywords

  • Gabor filter
  • Multi-phase texture segmentation
  • Mumford-Shah model
  • Wasserstein distance

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