Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance

Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance

Year:    2014

Communications in Computational Physics, Vol. 15 (2014), Iss. 5 : pp. 1480–1500

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.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.061212.111013a

Communications in Computational Physics, Vol. 15 (2014), Iss. 5 : pp. 1480–1500

Published online:    2014-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    21

Keywords: