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oai:docta.ucm.es:20.500.14352/534102024-11-27T14:04:48Zcom_20.500.14352_14col_20.500.14352_21

Painting algorithms for fuzzy classification Gómez González, Daniel Montero De Juan, Francisco Javier Yáñez Gestoso, Francisco Javier Poidomani, Carmelo Piscataway, N. J. 510.64 Fuzzy set theory Image classification Painting Remote sensing Lógica simbólica y matemática (Matemáticas) 1102.14 Lógica Simbólica Absfruct-Land cover analysis by means of remotely sensing images quite often suggest the existence of fuzzy classes, where no clear borders or particular shapes appear. In this paper we present an image classification aid algorithm which shows as its main output a processed image where each pixel is being colored according to the degree of similitude to their respective surrounding pixels. Such a processed image is therefore suggesting possible classes, to be implemented in a more sophisticated image classification process. A key underlying argument for this approach is the relevance of painting techniques in order to help decision makers to understand complex information relative to fuzzy image classification. Depto. de Estadística e Investigación Operativa Fac. de Ciencias Matemáticas TRUE pub 2023-06-20T13:41:39Z 2023-06-20T13:41:39Z 2004 book part https://hdl.handle.net/20.500.14352/53410 XXXX-XXXX 10.1109/FUZZY.2004.1375701 eng Gomez, D., Montero, J., Yanez, J., Poidomani, C.: Painting algorithms for fuzzy classification. En: 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542). pp. 127-132. IEEE, Budapest, Hungary (2004) open access application/pdf IEEE