An energy functional model by gradient vector-driven active contour for local fitted image segmentation
To design a gradient vector-driven active contour local fitted image segmentation model based on information entropy for analyzing the construction of the active contour model by the variational and level set methods for validating the proposed model theoretically and simulation experiments. Fir...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
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Wiley
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25829/7/An%20energy%20functional%20model%20by%20gradient.pdf http://umpir.ump.edu.my/id/eprint/25829/ https://doi.org/10.1111/bcpt.13266 |
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| _version_ | 1831526612984659968 |
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| author | Wang, Jing Hai, Tao M. Nomani, Kabir |
| author_facet | Wang, Jing Hai, Tao M. Nomani, Kabir |
| author_sort | Wang, Jing |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | To design a gradient vector-driven active contour
local fitted image segmentation model based on information
entropy for analyzing the construction of the active contour
model by the variational and level set methods for validating
the proposed model theoretically and simulation experiments. Firstly, several important active contour models
based on image boundary features are introduced, and the existing problems are analyzed in depth, and the causes of the problems are pointed out. Next, the non-conservative behavior of the gradient vector flow field is studied in depth, and an important conclusion about the flow field divergence of the gradient vector is obtained in the local fitted image segmentation model. On this basis, a new energy functional is constructed to measure the flux of the gradient vector flow field through the active curve, and transform the image segmentation problem into the minimum value of the energy functional. Finally, a new active contour model is constructed
using the gradient flow of the above energy functional. |
| format | Conference or Workshop Item |
| id | my.ump.umpir.25829 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2019 |
| publisher | Wiley |
| record_format | eprints |
| spelling | my.ump.umpir.258292019-12-23T01:09:05Z http://umpir.ump.edu.my/id/eprint/25829/ An energy functional model by gradient vector-driven active contour for local fitted image segmentation Wang, Jing Hai, Tao M. Nomani, Kabir QA76 Computer software To design a gradient vector-driven active contour local fitted image segmentation model based on information entropy for analyzing the construction of the active contour model by the variational and level set methods for validating the proposed model theoretically and simulation experiments. Firstly, several important active contour models based on image boundary features are introduced, and the existing problems are analyzed in depth, and the causes of the problems are pointed out. Next, the non-conservative behavior of the gradient vector flow field is studied in depth, and an important conclusion about the flow field divergence of the gradient vector is obtained in the local fitted image segmentation model. On this basis, a new energy functional is constructed to measure the flux of the gradient vector flow field through the active curve, and transform the image segmentation problem into the minimum value of the energy functional. Finally, a new active contour model is constructed using the gradient flow of the above energy functional. Wiley 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25829/7/An%20energy%20functional%20model%20by%20gradient.pdf Wang, Jing and Hai, Tao and M. Nomani, Kabir (2019) An energy functional model by gradient vector-driven active contour for local fitted image segmentation. In: BCPT, Basic & Clinical Pharmacology & Toxicology: 2019 Asia Pacific Conference on Medical and Health Science , 1-3 June 2019 , Seoul, South Korea. p. 218., 125 (S1). (Published) https://doi.org/10.1111/bcpt.13266 |
| spellingShingle | QA76 Computer software Wang, Jing Hai, Tao M. Nomani, Kabir An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title | An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title_full | An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title_fullStr | An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title_full_unstemmed | An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title_short | An energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| title_sort | energy functional model by gradient vector-driven active contour for local fitted image segmentation |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/25829/7/An%20energy%20functional%20model%20by%20gradient.pdf http://umpir.ump.edu.my/id/eprint/25829/ https://doi.org/10.1111/bcpt.13266 |
| url_provider | http://umpir.ump.edu.my/ |