Please use this identifier to cite or link to this item:
http://ri.uaemex.mx/handle20.500.11799/94746
Title: | Segmentation of images by color features: a survey | Authors: | Jair Cervantes Canales Farid García Lamont ASDRUBAL LOPEZ CHAU Lisbeth Rodríguez Mazahua |
Keywords: | Color spaces;Image segmentation;Quantitative evaluation;info:eu-repo/classification/cti/7 | Publisher: | Neurocomputing | Description: | En este articulo se hace la revisión del estado del arte sobre la segmentación de imagenes de color Image 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. |
URI: | http://ri.uaemex.mx/handle20.500.11799/94746 | Other Identifiers: | http://hdl.handle.net/20.500.11799/94746 | Rights: | info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0 |
Appears in Collections: | Producción |
Show full item record
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.