Department of Mathematics
Multi-phase texture segmentation using Gabor features histograms based on wasserstein distance
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. © 2014 Global-Science Press.
Gabor filter, Multi-phase texture segmentation, Mumford-Shah model, Wasserstein distance
Source Publication Title
Communications in Computational Physics
Global Science Press
Link to Publisher's Edition
Qiao, Motong, Wei Wang, and Michael Ng. "Multi-phase texture segmentation using Gabor features histograms based on wasserstein distance." Communications in Computational Physics 15.5 (2014): 1480-1500.