Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48805
DC FieldValueLanguage
dc.contributor.authorIssac, Ashishen_US
dc.contributor.authorMadan, Rishabhen_US
dc.contributor.authorDutta, Malay Kishoreen_US
dc.contributor.authorTravieso, Carlos M.en_US
dc.date.accessioned2018-11-24T01:05:10Z-
dc.date.available2018-11-24T01:05:10Z-
dc.date.issued2017en_US
dc.identifier.isbn9781509032518en_US
dc.identifier.urihttp://hdl.handle.net/10553/48805-
dc.description.abstractExudates are one of the abnormalities present in the eye which can lead to vision loss. Fundus images may consist of artifacts which occur during image acquisition and hamper the accuracy of detection of exudates. There is a need to develop an image processing based techniques for automated and correct segmentation of exudates from fundus images. This paper demonstrates an automatic computer vision algorithm for efficient identification of the exudates from fundus images by strategic fusion of techniques i.e. contrast normalization, top-hat transformation and average filtering. The proposed technique correctly detects exudates from the fundus images and rejects the artifacts and reflections. The average computation time for exudates segmentation from fundus images is 11 seconds. The proposed method is computationally efficient and robust and can be used for real time applications.en_US
dc.languageengen_US
dc.source2016 9th International Conference on Contemporary Computing, IC3 2016 (7880224)en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherFundus Imageen_US
dc.subject.otherExudatesen_US
dc.subject.otherDiabetic Retinopathyen_US
dc.subject.otherTop-Hat Transformen_US
dc.subject.otherAverage filteren_US
dc.subject.otherContrast adjustmenten_US
dc.titleAutomated detection of bright lesions from contrast normalized fundus imagesen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference9th International Conference on Contemporary Computing (IC3)en_US
dc.identifier.doi10.1109/IC3.2016.7880224en_US
dc.identifier.scopus85018480667-
dc.contributor.authorscopusid56800652200-
dc.contributor.authorscopusid57194048581-
dc.contributor.authorscopusid35291803600-
dc.contributor.authorscopusid6602376272-
dc.identifier.issue7880224-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.identifier.ulpgces
dc.contributor.buulpgcBU-TELen_US
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-4621-2768-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameTravieso González, Carlos Manuel-
crisitem.event.eventsstartdate11-08-2016-
crisitem.event.eventsenddate13-08-2016-
Appears in Collections:Actas de congresos
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