A novel level set approach for image segmentation with landmark constraints
Level set methods are widely used in image segmentation and shape analysis. However, most of the current research focuses on fast computational algorithms, initial value selection, and practical applications in various areas. To the best of our knowledge, no research has been conducted on segmentati...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/74448 |
| _version_ | 1848763277515948032 |
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| author | Pan, H. Liu, Wan-Quan Li, L. Zhou, Guanglu |
| author_facet | Pan, H. Liu, Wan-Quan Li, L. Zhou, Guanglu |
| author_sort | Pan, H. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Level set methods are widely used in image segmentation and shape analysis. However, most of the current research focuses on fast computational algorithms, initial value selection, and practical applications in various areas. To the best of our knowledge, no research has been conducted on segmentation with level set models where the segmentation contours have to pass through some prior landmark points. In this paper, we propose a new variational model for image segmentation based on the classical Chan-Vese model for this new problem. The new model incorporates prior landmarks information as constraints in a formulated optimization problem. Then, we investigate the theoretical solvability of the new model and design a new algorithm based on the Split Bregman algorithm for numerical implementation. Finally, we conduct some segmentation experiments on gray images and compare with the original Chan-Vese model. The obtained results show many advantages of the proposed model with broad applications. Additionally, we give some critical analysis of the proposed algorithm. |
| first_indexed | 2025-11-14T11:00:54Z |
| format | Journal Article |
| id | curtin-20.500.11937-74448 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:00:54Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-744482019-08-22T03:39:01Z A novel level set approach for image segmentation with landmark constraints Pan, H. Liu, Wan-Quan Li, L. Zhou, Guanglu Level set methods are widely used in image segmentation and shape analysis. However, most of the current research focuses on fast computational algorithms, initial value selection, and practical applications in various areas. To the best of our knowledge, no research has been conducted on segmentation with level set models where the segmentation contours have to pass through some prior landmark points. In this paper, we propose a new variational model for image segmentation based on the classical Chan-Vese model for this new problem. The new model incorporates prior landmarks information as constraints in a formulated optimization problem. Then, we investigate the theoretical solvability of the new model and design a new algorithm based on the Split Bregman algorithm for numerical implementation. Finally, we conduct some segmentation experiments on gray images and compare with the original Chan-Vese model. The obtained results show many advantages of the proposed model with broad applications. Additionally, we give some critical analysis of the proposed algorithm. 2019 Journal Article http://hdl.handle.net/20.500.11937/74448 10.1016/j.ijleo.2019.01.009 restricted |
| spellingShingle | Pan, H. Liu, Wan-Quan Li, L. Zhou, Guanglu A novel level set approach for image segmentation with landmark constraints |
| title | A novel level set approach for image segmentation with landmark constraints |
| title_full | A novel level set approach for image segmentation with landmark constraints |
| title_fullStr | A novel level set approach for image segmentation with landmark constraints |
| title_full_unstemmed | A novel level set approach for image segmentation with landmark constraints |
| title_short | A novel level set approach for image segmentation with landmark constraints |
| title_sort | novel level set approach for image segmentation with landmark constraints |
| url | http://hdl.handle.net/20.500.11937/74448 |