Image Segmentation Using Excess Entropy

We present a novel information-theoretic approach for thresholding-based segmentation that uses the excess entropy to measure the structural information of a 2D or 3D image and to locate the optimal thresholds. This approach is based on the conjecture that the optimal thresholding corresponds to the...

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Detalhes bibliográficos
Autores: Bardera i Reig, Antoni, Boada, Imma, Feixas Feixas, Miquel, Sbert, Mateu
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2009
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/21517
Acesso em linha:http://hdl.handle.net/10256/21517
Access Level:acceso abierto
Palavra-chave:Imatgeria (Tècnica)
Imaging systems
Imatges -- Processament
Image processing
Imatgeria tridimensional
Three-dimensional imaging
Imatges -- Segmentació
Imaging segmentation
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network_name_str España
repository_id_str
spelling Image Segmentation Using Excess EntropyBardera i Reig, AntoniBoada, ImmaFeixas Feixas, MiquelSbert, MateuImatgeria (Tècnica)Imaging systemsImatges -- ProcessamentImage processingImatgeria tridimensionalThree-dimensional imagingImatges -- SegmentacióImaging segmentationWe present a novel information-theoretic approach for thresholding-based segmentation that uses the excess entropy to measure the structural information of a 2D or 3D image and to locate the optimal thresholds. This approach is based on the conjecture that the optimal thresholding corresponds to the segmentation with maximum structure, i.e., maximum excess entropy. The contributions of this paper are several fold. First, we introduce the excess entropy as a measure of the spatial structure of an image. Second, we present an adaptive thresholding method based on the maximization of excess entropy. Third, we propose the use of uniformly distributed random lines to overcome the main drawbacks of the excess entropy computation. To show the good performance of the proposed segmentation approach different experiments on synthetic and real brain models are carried outSpringer2009info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionpeer-reviewed10 p.application/pdfhttp://hdl.handle.net/10256/21517http://hdl.handle.net/10256/21517© Journal of Signal Processing Systems for Signal, Image, and Video Technology, 2009, vol. 54, num. 1-3, p. 205-214Articles publicats (D-IMAE)Bardera i Reig, Antoni Boada, Imma Feixas Feixas, Miquel Sbert, Mateu 2009 Image Segmentation Using Excess Entropy Journal of Signal Processing Systems for Signal, Image, and Video Technology 54 1-3 205 214reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1007/s11265-008-0194-6info:eu-repo/semantics/altIdentifier/issn/1939-8018info:eu-repo/semantics/altIdentifier/eissn/1939-8115Tots els drets reservatsinfo:eu-repo/semantics/openAccessoai:recercat.cat:10256/215172026-05-29T05:05:01Z
dc.title.none.fl_str_mv Image Segmentation Using Excess Entropy
title Image Segmentation Using Excess Entropy
spellingShingle Image Segmentation Using Excess Entropy
Bardera i Reig, Antoni
Imatgeria (Tècnica)
Imaging systems
Imatges -- Processament
Image processing
Imatgeria tridimensional
Three-dimensional imaging
Imatges -- Segmentació
Imaging segmentation
title_short Image Segmentation Using Excess Entropy
title_full Image Segmentation Using Excess Entropy
title_fullStr Image Segmentation Using Excess Entropy
title_full_unstemmed Image Segmentation Using Excess Entropy
title_sort Image Segmentation Using Excess Entropy
dc.creator.none.fl_str_mv Bardera i Reig, Antoni
Boada, Imma
Feixas Feixas, Miquel
Sbert, Mateu
author Bardera i Reig, Antoni
author_facet Bardera i Reig, Antoni
Boada, Imma
Feixas Feixas, Miquel
Sbert, Mateu
author_role author
author2 Boada, Imma
Feixas Feixas, Miquel
Sbert, Mateu
author2_role author
author
author
dc.subject.none.fl_str_mv Imatgeria (Tècnica)
Imaging systems
Imatges -- Processament
Image processing
Imatgeria tridimensional
Three-dimensional imaging
Imatges -- Segmentació
Imaging segmentation
topic Imatgeria (Tècnica)
Imaging systems
Imatges -- Processament
Image processing
Imatgeria tridimensional
Three-dimensional imaging
Imatges -- Segmentació
Imaging segmentation
description We present a novel information-theoretic approach for thresholding-based segmentation that uses the excess entropy to measure the structural information of a 2D or 3D image and to locate the optimal thresholds. This approach is based on the conjecture that the optimal thresholding corresponds to the segmentation with maximum structure, i.e., maximum excess entropy. The contributions of this paper are several fold. First, we introduce the excess entropy as a measure of the spatial structure of an image. Second, we present an adaptive thresholding method based on the maximization of excess entropy. Third, we propose the use of uniformly distributed random lines to overcome the main drawbacks of the excess entropy computation. To show the good performance of the proposed segmentation approach different experiments on synthetic and real brain models are carried out
publishDate 2009
dc.date.none.fl_str_mv 2009
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
peer-reviewed
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/21517
http://hdl.handle.net/10256/21517
url http://hdl.handle.net/10256/21517
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s11265-008-0194-6
info:eu-repo/semantics/altIdentifier/issn/1939-8018
info:eu-repo/semantics/altIdentifier/eissn/1939-8115
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10 p.
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv © Journal of Signal Processing Systems for Signal, Image, and Video Technology, 2009, vol. 54, num. 1-3, p. 205-214
Articles publicats (D-IMAE)
Bardera i Reig, Antoni Boada, Imma Feixas Feixas, Miquel Sbert, Mateu 2009 Image Segmentation Using Excess Entropy Journal of Signal Processing Systems for Signal, Image, and Video Technology 54 1-3 205 214
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869412297093414912
score 15.198674

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