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Título

Classifying image analysis techniques from their output

AutorGuada, Carely; Gómez, Daniel; Tinguaro Rodríguez, J.; Yáñez, Javier; Montero, Javier CSIC ORCID
Palabras claveImage segmentation
Image classification
Edge detection
Fuzzy sets
Machine learning
Graphs
Fecha de publicación26-abr-2016
EditorTaylor & Francis
CitaciónInternational Journal of Computational Intelligence Systems, 9 (Supplement 1): 43-68 (2016)
ResumenIn this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some stage, each technique has been usually designed to focus on a specific objective, and their outputs are in fact different according to each objective. Thus, they are in fact different methods. But due to the essential relationship between them they are quite often confused. In particular, this paper pursues a clarification of the differences between image segmentation and edge detection, among other image processing techniques.
Versión del editorhttp://dx.doi.org/10.1080/18756891.2016.1180819
URIhttp://hdl.handle.net/10261/132433
DOI10.1080/18756891.2016.1180819
ISSN1875-6891
E-ISSN1875-6883
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