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


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

Motong Qiao 1*, Wei Wang 2, Michael Ng 3

1 Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
2 Department of Mathematics, Tongji University, Shanghai 200092, China.
3 Centre for Mathematical Imaging and Vision and Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong.

Received 6 December 2012; Accepted (in revised version) 11 October 2013
Available online 14 March 2014
doi:10.4208/cicp.061212.111013a

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.

AMS subject classifications: 68U10

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Key words: Multi-phase texture segmentation, Wasserstein distance, Gabor filter, Mumford-Shah model.

*Corresponding author.
Email: qiao.motong@gmail.com (M. Qiao)
 

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