Please use this identifier to cite or link to this item: http://ri.uaemex.mx/handle20.500.11799/94746
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dc.contributor.authorJair Cervantes Canalesen_EU
dc.contributor.authorFarid García Lamonten_EU
dc.contributor.authorASDRUBAL LOPEZ CHAUen_EU
dc.contributor.authorLisbeth Rodríguez Mazahuaen_EU
dc.creatorJair Cervantes Canales-
dc.creatorFarid García Lamont-
dc.creatorASDRUBAL LOPEZ CHAU-
dc.creatorLisbeth Rodríguez Mazahua-
dc.date2018-05-31-
dc.date.accessioned2019-03-12T23:44:14Z-
dc.date.available2019-03-12T23:44:14Z-
dc.identifierhttp://hdl.handle.net/20.500.11799/94746-
dc.identifier.urihttp://ri.uaemex.mx/handle20.500.11799/94746-
dc.descriptionEn este articulo se hace la revisión del estado del arte sobre la segmentación de imagenes de color-
dc.descriptionImage segmentation is an important stage for object recognition. Many methods have been proposed in the last few years for grayscale and color images. In this paper, we present a deep review of the state of the art on color image segmentation methods; through this paper, we explain the techniques based on edge detection, thresholding, histogram-thresholding, region, feature clustering and neural networks. Because color spaces play a key role in the methods reviewed, we also explain in detail the most commonly color spaces to represent and process colors. In addition, we present some important applications that use the methods of image segmentation reviewed. Finally, a set of metrics frequently used to evaluate quantitatively the segmented images is shown.-
dc.languageeng-
dc.publisherNeurocomputing-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttp://creativecommons.org/licenses/by/4.0-
dc.source0925-2312-
dc.subjectColor spaces-
dc.subjectImage segmentation-
dc.subjectQuantitative evaluation-
dc.subjectinfo:eu-repo/classification/cti/7-
dc.titleSegmentation of images by color features: a survey-
dc.typebookPart-
dc.audiencestudents-
dc.audienceresearchers-
item.grantfulltextnone-
item.fulltextNo Fulltext-
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