Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information
Active contour models are used to extract object boundary from digital image, but there is poor convergence for the targets with deep concavities. We proposed an improved approach based on existing gradient vector flow methods. Main contributions of this paper are a new algorithm to determine the f...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/479675 |
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| _version_ | 1832564268234440704 |
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| author | Jianhui Zhao Bingyu Chen Mingui Sun Wenyan Jia Zhiyong Yuan |
| author_facet | Jianhui Zhao Bingyu Chen Mingui Sun Wenyan Jia Zhiyong Yuan |
| author_sort | Jianhui Zhao |
| collection | DOAJ |
| description | Active contour models are used to extract object boundary from digital image, but there is poor convergence for the targets with deep concavities. We proposed an improved approach based on existing gradient vector flow methods. Main contributions of this paper are a new algorithm to determine the false part of active contour with higher accuracy from the global force of gradient vector flow and a new algorithm to update the external force field together with the local information of magnetostatic force. Our method has a semidynamic external force field, which is adjusted only when the false active contour exists. Thus, active contours have more chances to approximate the complex boundary, while the computational cost is limited effectively. The new algorithm is tested on irregular shapes and then on real images such as MRI and ultrasound medical data. Experimental results illustrate the efficiency of our method, and the computational complexity is also analyzed. |
| format | Article |
| id | doaj-art-75a3f4acf3064c9a95abf9aa06521904 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-75a3f4acf3064c9a95abf9aa065219042025-02-03T01:11:24ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/479675479675Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local InformationJianhui Zhao0Bingyu Chen1Mingui Sun2Wenyan Jia3Zhiyong Yuan4School of Computer, Wuhan University, Wuhan, Hubei 430072, ChinaSchool of Computer, Wuhan University, Wuhan, Hubei 430072, ChinaDepartment of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USADepartment of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USASchool of Computer, Wuhan University, Wuhan, Hubei 430072, ChinaActive contour models are used to extract object boundary from digital image, but there is poor convergence for the targets with deep concavities. We proposed an improved approach based on existing gradient vector flow methods. Main contributions of this paper are a new algorithm to determine the false part of active contour with higher accuracy from the global force of gradient vector flow and a new algorithm to update the external force field together with the local information of magnetostatic force. Our method has a semidynamic external force field, which is adjusted only when the false active contour exists. Thus, active contours have more chances to approximate the complex boundary, while the computational cost is limited effectively. The new algorithm is tested on irregular shapes and then on real images such as MRI and ultrasound medical data. Experimental results illustrate the efficiency of our method, and the computational complexity is also analyzed.http://dx.doi.org/10.1155/2013/479675 |
| spellingShingle | Jianhui Zhao Bingyu Chen Mingui Sun Wenyan Jia Zhiyong Yuan Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information The Scientific World Journal |
| title | Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information |
| title_full | Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information |
| title_fullStr | Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information |
| title_full_unstemmed | Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information |
| title_short | Improved Algorithm for Gradient Vector Flow Based Active Contour Model Using Global and Local Information |
| title_sort | improved algorithm for gradient vector flow based active contour model using global and local information |
| url | http://dx.doi.org/10.1155/2013/479675 |
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