Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions

Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions

In this paper, an image segmentation method based on Dempster-Shafer evidence theory is proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. No assumption is made about the images data distribution. bpa is e...

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Bibliographic Details
Main Authors: Abdel-Ouahab Boudraa, Ayachi Bentabet, Fabien Salzenstein
Format: Article
Language:English
Published: Computer Vision Center Press 2004-04-01
Series:ELCVIA Electronic Letters on Computer Vision and Image Analysis
Subjects:
image segmentation and image extraction
Data fusion
Basic probability assignment
Demspter-Shafer evidence
Online Access:https://elcvia.cvc.uab.es/article/view/68
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spelling doaj-628ce6c4d9f14a5fab00be1c3425ff172021-09-18T12:41:13ZengComputer Vision Center PressELCVIA Electronic Letters on Computer Vision and Image Analysis1577-50972004-04-014110.5565/rev/elcvia.6840Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership FunctionsAbdel-Ouahab BoudraaAyachi BentabetFabien SalzensteinIn this paper, an image segmentation method based on Dempster-Shafer evidence theory is proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. No assumption is made about the images data distribution. bpa is estimated at pixel level. The effectiveness of the method is demonstrated on synthetic and real images.¡https://elcvia.cvc.uab.es/article/view/68image segmentation and image extractionData fusionBasic probability assignmentDemspter-Shafer evidence
collection DOAJ
language English
format Article
sources DOAJ
author Abdel-Ouahab Boudraa
Ayachi Bentabet
Fabien Salzenstein
spellingShingle Abdel-Ouahab Boudraa
Ayachi Bentabet
Fabien Salzenstein
Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
ELCVIA Electronic Letters on Computer Vision and Image Analysis
image segmentation and image extraction
Data fusion
Basic probability assignment
Demspter-Shafer evidence
author_facet Abdel-Ouahab Boudraa
Ayachi Bentabet
Fabien Salzenstein
author_sort Abdel-Ouahab Boudraa
title Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
title_short Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
title_full Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
title_fullStr Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
title_full_unstemmed Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions
title_sort dempster-shafer's basic probability assignment based on fuzzy membership functions
publisher Computer Vision Center Press
series ELCVIA Electronic Letters on Computer Vision and Image Analysis
issn 1577-5097
publishDate 2004-04-01
description In this paper, an image segmentation method based on Dempster-Shafer evidence theory is proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. No assumption is made about the images data distribution. bpa is estimated at pixel level. The effectiveness of the method is demonstrated on synthetic and real images.¡
topic image segmentation and image extraction
Data fusion
Basic probability assignment
Demspter-Shafer evidence
url https://elcvia.cvc.uab.es/article/view/68
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AT ayachibentabet dempstershafersbasicprobabilityassignmentbasedonfuzzymembershipfunctions
AT fabiensalzenstein dempstershafersbasicprobabilityassignmentbasedonfuzzymembershipfunctions
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