Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem

The segmentation of weak boundary is still a difficult problem, especially sensitive to noise, which leads to the failure of segmentation. Based on the previous works, by adding the boundary indicator function with L2,1 norm, a new convergent variational model is proposed. A novel strategy for the w...

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Main Authors: Ran Gao, Li-Zhen Guo
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2021/2852399
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author Ran Gao
Li-Zhen Guo
author_facet Ran Gao
Li-Zhen Guo
author_sort Ran Gao
collection DOAJ
description The segmentation of weak boundary is still a difficult problem, especially sensitive to noise, which leads to the failure of segmentation. Based on the previous works, by adding the boundary indicator function with L2,1 norm, a new convergent variational model is proposed. A novel strategy for the weak boundary image is presented. The existence of the minimizer for our model is given, by using the alternating direction method of multipliers (ADMMs) to solve the model. The experiments show that our new method is robust in segmentation of objects in a range of images with noise, low contrast, and direction.
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institution Kabale University
issn 1607-887X
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-987801479c6d41129a772e644fb709fc2025-02-03T07:24:16ZengWileyDiscrete Dynamics in Nature and Society1607-887X2021-01-01202110.1155/2021/2852399Fast Global Minimization of the Chan–Vese Model for Image Segmentation ProblemRan Gao0Li-Zhen Guo1College of ScienceSchool of Mathematics and StatisticsThe segmentation of weak boundary is still a difficult problem, especially sensitive to noise, which leads to the failure of segmentation. Based on the previous works, by adding the boundary indicator function with L2,1 norm, a new convergent variational model is proposed. A novel strategy for the weak boundary image is presented. The existence of the minimizer for our model is given, by using the alternating direction method of multipliers (ADMMs) to solve the model. The experiments show that our new method is robust in segmentation of objects in a range of images with noise, low contrast, and direction.http://dx.doi.org/10.1155/2021/2852399
spellingShingle Ran Gao
Li-Zhen Guo
Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
Discrete Dynamics in Nature and Society
title Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
title_full Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
title_fullStr Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
title_full_unstemmed Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
title_short Fast Global Minimization of the Chan–Vese Model for Image Segmentation Problem
title_sort fast global minimization of the chan vese model for image segmentation problem
url http://dx.doi.org/10.1155/2021/2852399
work_keys_str_mv AT rangao fastglobalminimizationofthechanvesemodelforimagesegmentationproblem
AT lizhenguo fastglobalminimizationofthechanvesemodelforimagesegmentationproblem