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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Format: | Article |
Language: | English |
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Wiley
2021-01-01
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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. |
format | Article |
id | doaj-art-987801479c6d41129a772e644fb709fc |
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 |