Mostrar el registro sencillo del ítem

Artículo

dc.creatorDíaz Pernil, Danieles
dc.creatorFondón García, Irenees
dc.creatorPeña Cantillana, Franciscoes
dc.creatorGutiérrez Naranjo, Miguel Ángeles
dc.date.accessioned2018-05-14T09:48:47Z
dc.date.available2018-05-14T09:48:47Z
dc.date.issued2016-11
dc.identifier.citationDíaz Pernil, D., Fondón García, I., Peña Cantillana, F. y Gutiérrez Naranjo, M.Á. (2016). Fully automatized parallel segmentation of the optic disc in retinal fundus images. Pattern Recognition Letters, 83 (1), 99-107.
dc.identifier.issn0167-8655es
dc.identifier.urihttps://hdl.handle.net/11441/74559
dc.description.abstractThis paper presents a fully automatic parallel software for the localization of the optic disc (OD) in retinal fundus color images. A new method has been implemented with the Graphics Processing Units (GPU) technology. Image edges are extracted using a new operator, called AGP-color segmentator. The resulting image is binarized with Hamadani’s technique and, finally, a new algorithm called Hough circle cloud is applied for the detection of the OD. The reliability of the tool has been tested with 129 images from the public databases DRIVE and DIARETDB1 obtaining an average accuracy of 99.6% and a mean consumed time per image of 7.6 and 16.3 s respectively. A comparison with several state-of-the-art algorithms shows that our algorithm represents a significant improvement in terms of accuracy and efficiency.es
dc.description.sponsorshipMinisterio de Economía y Competitividad TIN2012-37434es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofPattern Recognition Letters, 83 (1), 99-107.
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectOptic disces
dc.subjectHough transformes
dc.subjectParallel image processinges
dc.subjectGPUes
dc.titleFully automatized parallel segmentation of the optic disc in retinal fundus imageses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Matemática Aplicada Ies
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Teoría de la Señal y Comunicacioneses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDTIN2012-37434es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0167865516300794es
dc.identifier.doi10.1016/j.patrec.2016.04.025es
dc.contributor.groupUniversidad de Sevilla. FQM296:Topología Computacional y Matemática Aplicadaes
dc.contributor.groupUniversidad de Sevilla. TIC193: Computacion Naturales
idus.format.extent9es
dc.journaltitlePattern Recognition Letterses
dc.publication.volumen83es
dc.publication.issue1es
dc.publication.initialPage99es
dc.publication.endPage107es
dc.identifier.sisius21027019es
dc.contributor.funderMinisterio de Economía y Competitividad (MINECO). España

FicherosTamañoFormatoVerDescripción
Fully automatized parallel.pdf2.954MbIcon   [PDF] Ver/Abrir  

Este registro aparece en las siguientes colecciones

Mostrar el registro sencillo del ítem

Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
Excepto si se señala otra cosa, la licencia del ítem se describe como: Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América