Local image fitting-based active contour for vector-valued images

Variational active contour seeks to segment or extract desired object boundaries for further analysis. The model can be divided into global segmentation and selective segmentation. Selective segmentation, which focuses on segmenting a particular object, is preferable to the global model. Recently, a...

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Published in:Indonesian Journal of Electrical Engineering and Computer Science
Main Author: Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174162808&doi=10.11591%2fijeecs.v32.i1.pp227-235&partnerID=40&md5=9a5535a880630d0e63cfb6995bed83c5
id 2-s2.0-85174162808
spelling 2-s2.0-85174162808
Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
Local image fitting-based active contour for vector-valued images
2023
Indonesian Journal of Electrical Engineering and Computer Science
32
1
10.11591/ijeecs.v32.i1.pp227-235
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174162808&doi=10.11591%2fijeecs.v32.i1.pp227-235&partnerID=40&md5=9a5535a880630d0e63cfb6995bed83c5
Variational active contour seeks to segment or extract desired object boundaries for further analysis. The model can be divided into global segmentation and selective segmentation. Selective segmentation, which focuses on segmenting a particular object, is preferable to the global model. Recently, a number of selective segmentation models have been developed to precisely extract an object on grayscale images. Nevertheless, if the input image is vector-valued (colour), these models merely convert it to a grayscale image, resulting in data loss owing to the reduction in image dimension. Furthermore, they may have poor segmentation performance due to the intensity inhomogeneous images. Therefore, a new model on variational selective active contour for segmenting vector-valued images has been proposed that incorporates the concepts of local image fitting and distance-based fitting terms into a variational minimization energy functional. Moreover, a Gaussian function was used as a regularizer to replace the computationally expensive Total Variation term. Then, the proposed model’s Euler Lagrange equation has been provided to solve the model. When segmenting an object in inhomogeneous intensity images, the result of the proposed model was about 30% more accurate based on the Jaccard value and about 3 times faster than other existing methods. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
Institute of Advanced Engineering and Science
25024752
English
Article
All Open Access; Gold Open Access; Green Open Access
author Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
spellingShingle Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
Local image fitting-based active contour for vector-valued images
author_facet Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
author_sort Azam A.S.B.; Jumaat A.K.; Maasar M.A.; Laham M.F.; Rahman N.N.A.
title Local image fitting-based active contour for vector-valued images
title_short Local image fitting-based active contour for vector-valued images
title_full Local image fitting-based active contour for vector-valued images
title_fullStr Local image fitting-based active contour for vector-valued images
title_full_unstemmed Local image fitting-based active contour for vector-valued images
title_sort Local image fitting-based active contour for vector-valued images
publishDate 2023
container_title Indonesian Journal of Electrical Engineering and Computer Science
container_volume 32
container_issue 1
doi_str_mv 10.11591/ijeecs.v32.i1.pp227-235
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174162808&doi=10.11591%2fijeecs.v32.i1.pp227-235&partnerID=40&md5=9a5535a880630d0e63cfb6995bed83c5
description Variational active contour seeks to segment or extract desired object boundaries for further analysis. The model can be divided into global segmentation and selective segmentation. Selective segmentation, which focuses on segmenting a particular object, is preferable to the global model. Recently, a number of selective segmentation models have been developed to precisely extract an object on grayscale images. Nevertheless, if the input image is vector-valued (colour), these models merely convert it to a grayscale image, resulting in data loss owing to the reduction in image dimension. Furthermore, they may have poor segmentation performance due to the intensity inhomogeneous images. Therefore, a new model on variational selective active contour for segmenting vector-valued images has been proposed that incorporates the concepts of local image fitting and distance-based fitting terms into a variational minimization energy functional. Moreover, a Gaussian function was used as a regularizer to replace the computationally expensive Total Variation term. Then, the proposed model’s Euler Lagrange equation has been provided to solve the model. When segmenting an object in inhomogeneous intensity images, the result of the proposed model was about 30% more accurate based on the Jaccard value and about 3 times faster than other existing methods. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
publisher Institute of Advanced Engineering and Science
issn 25024752
language English
format Article
accesstype All Open Access; Gold Open Access; Green Open Access
record_format scopus
collection Scopus
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