| Título: | A coloring fuzzy graph approach for image classification. |
| Autores: | Gomez, D. ; Montero, Javier ; Yáñez, Javier |
| Tipo de documento: | texto impreso |
| Editorial: | Elsevier Science INC, 2006 |
| Dimensiones: | application/pdf |
| Nota general: | info:eu-repo/semantics/restrictedAccess |
| Idiomas: | |
| Palabras clave: | Estado = Publicado , Materia = Ciencias: Informática: Inteligencia artificial , Tipo = Artículo |
| Resumen: |
One of the main problems in practice is the difficulty in dealing with membership functions. Many decision makers ask for a graphical representation to help them to visualize results. In this paper, we point out that some useful tools for fuzzy classification can be derived from fuzzy coloring procedures. In particular, we bring here a crisp grey coloring algorithm based upon a sequential application of a basic black and white binary coloring procedure, already introduced in a previous paper [D. Gomez, J. Montero, J. Yañez, C. Poidomani, A graph coloring algorithm approach for image segmentation, Omega, in press]. In this article, the image is conceived as a fuzzy graph defined on the set of pixels where fuzzy edges represent the distance between pixels. In this way,we can obtain a more flexible hierarchical structure of colors, which in turn should give useful hints about those classes with unclear boundaries. |
| En línea: | https://eprints.ucm.es/id/eprint/16677/1/Montero40.pdf |
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