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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: Wang, Jing, Hai, Tao, M. Nomani, Kabir
Format: Conference or Workshop Item
Language:English
Published: Wiley 2019
Subjects:
QA76 Computer software
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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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). https://doi.org/10.1111/bcpt.13266
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA76 Computer software
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
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
author Wang, Jing
Hai, Tao
M. Nomani, Kabir
author_facet Wang, Jing
Hai, Tao
M. Nomani, Kabir
author_sort Wang, Jing
title 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_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_sort energy functional model by gradient vector-driven active contour for local fitted image segmentation
publisher Wiley
publishDate 2019
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
_version_ 1654960224809779200
score 13.211869

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