A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts
This paper presents a novel Markov random field (MRF) and adaptive regularization embedded level set model for robust image segmentation and uses graph cuts optimization to numerically solve it. Firstly, a special MRF-based energy term in the form of level set formulation is constructed for strong l...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/8747385 |
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| _version_ | 1841524781901414400 |
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| author | Dengwei Wang |
| author_facet | Dengwei Wang |
| author_sort | Dengwei Wang |
| collection | DOAJ |
| description | This paper presents a novel Markov random field (MRF) and adaptive regularization embedded level set model for robust image segmentation and uses graph cuts optimization to numerically solve it. Firstly, a special MRF-based energy term in the form of level set formulation is constructed for strong local neighborhood modeling. Secondly, a regularization constraint with adaptive properties is imposed onto the proposed model with the following purposes: reduce the influence of noise, force the power exponent of the regularization process to change adaptively with image coordinates, and ensure the active contour does not pass through the weak object boundaries. Thirdly, graph cuts optimization is used to implement the numerical solution of the proposed model to obtain extremely fast convergence performance. The extensive and promising experimental results on wide variety of images demonstrate the excellent performance of the proposed method in both segmentation accuracy and convergence rate. |
| format | Article |
| id | doaj-art-622923b065b149139252fab6eb11743f |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-622923b065b149139252fab6eb11743f2025-02-03T05:47:20ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552019-01-01201910.1155/2019/87473858747385A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph CutsDengwei Wang0School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, ChinaThis paper presents a novel Markov random field (MRF) and adaptive regularization embedded level set model for robust image segmentation and uses graph cuts optimization to numerically solve it. Firstly, a special MRF-based energy term in the form of level set formulation is constructed for strong local neighborhood modeling. Secondly, a regularization constraint with adaptive properties is imposed onto the proposed model with the following purposes: reduce the influence of noise, force the power exponent of the regularization process to change adaptively with image coordinates, and ensure the active contour does not pass through the weak object boundaries. Thirdly, graph cuts optimization is used to implement the numerical solution of the proposed model to obtain extremely fast convergence performance. The extensive and promising experimental results on wide variety of images demonstrate the excellent performance of the proposed method in both segmentation accuracy and convergence rate.http://dx.doi.org/10.1155/2019/8747385 |
| spellingShingle | Dengwei Wang A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts Journal of Electrical and Computer Engineering |
| title | A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts |
| title_full | A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts |
| title_fullStr | A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts |
| title_full_unstemmed | A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts |
| title_short | A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts |
| title_sort | markov random field and adaptive regularization embedded level set segmentation model solving by graph cuts |
| url | http://dx.doi.org/10.1155/2019/8747385 |
| work_keys_str_mv | AT dengweiwang amarkovrandomfieldandadaptiveregularizationembeddedlevelsetsegmentationmodelsolvingbygraphcuts AT dengweiwang markovrandomfieldandadaptiveregularizationembeddedlevelsetsegmentationmodelsolvingbygraphcuts |