Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Kernel density estimation based multiphase fuzzy region competition method for texture image segmentation

Language

English

Abstract

In this paper, we propose a multiphase fuzzy region competition model for texture image segmentation. In the functional, each region is represented by a fuzzy membership function and a probability density function that is estimated by a nonparametric kernel density estimation. The overall algorithmis very efficient as both the fuzzy membership function and the probability density function can be implemented easily. We apply the proposed method to synthetic and natural texture images, and synthetic aperture radar images. Our experimental results have shown that the proposed method is competitive with the other state-of-the-art segmentation methods. © 2010 Global-Science Press.

Keywords

Fuzzy membership function, Kernel density estimation, Multiphase region competition, Texture, Total variation

Publication Date

2010

Source Publication Title

Communications in Computational Physics

Volume

8

Issue

3

Start Page

623

End Page

641

Publisher

Global Science Press

DOI

10.4208/cicp.160609.311209a

Link to Publisher's Edition

http://dx.doi.org/10.4208/cicp.160609.311209a

ISSN (print)

18152406

ISSN (electronic)

19917120

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