@Article{CiCP-15-5,
author = {},
title = {Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance},
journal = {Communications in Computational Physics},
year = {2014},
volume = {15},
number = {5},
pages = {1480--1500},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.061212.111013a},
url = {https://global-sci.com/article/80543/multi-phase-texture-segmentation-using-gabor-features-histograms-based-on-wasserstein-distance}
}