Volume 15, Issue 5
Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance

Motong Qiao, Wei Wang & Michael Ng

Commun. Comput. Phys., 15 (2014), pp. 1480-1500.

Published online: 2014-05

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  • 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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@Article{CiCP-15-1480, 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 = {

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.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.061212.111013a}, url = {http://global-sci.org/intro/article_detail/cicp/7146.html} }
TY - JOUR T1 - Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance JO - Communications in Computational Physics VL - 5 SP - 1480 EP - 1500 PY - 2014 DA - 2014/05 SN - 15 DO - http://doi.org/10.4208/cicp.061212.111013a UR - https://global-sci.org/intro/article_detail/cicp/7146.html KW - AB -

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.

Motong Qiao, Wei Wang & Michael Ng. (2020). Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance. Communications in Computational Physics. 15 (5). 1480-1500. doi:10.4208/cicp.061212.111013a
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