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/ http://umpir.ump.edu.my/id/eprint/25829/ http://umpir.ump.edu.my/id/eprint/25829/7/An%20energy%20functional%20model%20by%20gradient.pdf

id	ump-25829
recordtype	eprints
spelling	ump-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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
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/ http://umpir.ump.edu.my/id/eprint/25829/ http://umpir.ump.edu.my/id/eprint/25829/7/An%20energy%20functional%20model%20by%20gradient.pdf
first_indexed	2023-09-18T22:39:53Z
last_indexed	2023-09-18T22:39:53Z
_version_	1777416843621826560

An energy functional model by gradient vector-driven active contour for local fitted image segmentation

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