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Painting algorithms for fuzzy classification

dc.book.titleFuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
dc.contributor.authorGómez González, Daniel
dc.contributor.authorMontero De Juan, Francisco Javier
dc.contributor.authorYáñez Gestoso, Francisco Javier
dc.contributor.authorPoidomani, Carmelo
dc.contributor.editorPiscataway, N. J.
dc.date.accessioned2023-06-20T13:41:39Z
dc.date.available2023-06-20T13:41:39Z
dc.date.issued2004
dc.description.abstractAbsfruct-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.en
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/29111
dc.identifier.citationGomez, 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)
dc.identifier.doi10.1109/FUZZY.2004.1375701
dc.identifier.isbn0-7803-8353-2
dc.identifier.officialurlhttps//doi.org/10.1109/FUZZY.2004.1375701
dc.identifier.relatedurlhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1375701&abstractAccess=no&userType=inst
dc.identifier.urihttps://hdl.handle.net/20.500.14352/53410
dc.language.isoeng
dc.page.final132
dc.page.initial127
dc.publisherIEEE
dc.rights.accessRightsopen access
dc.subject.cdu510.64
dc.subject.keywordFuzzy set theory
dc.subject.keywordImage classification
dc.subject.keywordPainting
dc.subject.keywordRemote sensing
dc.subject.ucmLógica simbólica y matemática (Matemáticas)
dc.subject.unesco1102.14 Lógica Simbólica
dc.titlePainting algorithms for fuzzy classificationen
dc.typebook part
dc.volume.number1
dcterms.referencesA. Amo, D. Gómez, J. Montero and G. Biging: "Relevance and redundancy in fuzzy classification systems," Mathware and Soft Computing 8, 203-216 (2001). A. Amo, J. Montero and G. Biging: "Classifying pixels by means of fuzzy relations," International Journal of General Systems 29, 605-621 (2000). A. Amo, J. Montero, G. Biging and V. Cutello: "Fuzzy classification systems," European Journal of Operational Research 156, 495-507 (2004). A. Amo, J. Montero and V. Cutello: "On the principles of fuzzy classification," Proceedings of the annual North American Fuzzy Information Processing Society conference (NAFIPS); pp. 675-679 (1999). A. Amo, J. Montero, A. Fernández, M. López, J. Tordesillas and G. Biging: "Spectral fuzzy classification: an application," IEEE Transactions on Systems Man and ybernetics (C) 32, 42-48 (2002). J.C. Bezdek: Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981. J.C. Bezdek and J.D. Harris: "Fuzzy partitions and relations: an axiomatic basis for clustering," Fuzzy Sets and Systems 1, 111-127 (1978). G.M. Foody: "The continuum of classification fuzziness in thematics mapping," Photogrammetric Engineering and Remote Sensing 65, 443-451 (1999). D. Gómez, J. Montero, J. Yáñez and C. Poidomani: "A Coloring Algorithm for Image Classification," Proceedings of Fuzzy Logic in Nuclear Science conference, F.L.I.N.S. (Blankenberghe, Belgium, September 1-4, 2004). D. Gómez, J. Montero, J. Yáñez and C. Poidomani: "A fuzzy graph coloring algorithm for image classification," Technical Report. Department of Statistics and Operational Research, Faculty of Mathematics, Complutense University of Madrid, Spain (2004). J. R. Jensen: Introductory Digital Image Processing. A Remote Sensing Perspective, Prentice Hall, New York, 1996. E.E. Kerre and M. Nachtegael: Fuzzy Techniques in Image Processing, Physica-Verlag, Heidelberg, 2000. L. Kóczy: "Fuzzy graphs in the evaluation and optimization of netwoks," Fuzzy sets and systems 46:307-319 (1992). J. Montero, A. Pearman and J. Tejada: "Fuzzy multicriteria decision support for budget allocation in the transport sector," TOP 3:47-68 (1995). J.N. Mordeson and S. Nair: Fuzzy graphs and Fuzzy Hypergraphs, Physica-Verlag, Heidelberg, 2000. S.K. Pal, A. Ghosh and M.K. Kundu: Soft Computing for Image Processing, Physica-Verlag, Heidelberg, 2000. P.M. Pardalos, T. Mavridou and J. Xue: "The Graph Coloring Problem: A Bibliographic Survey". In: D.Z. Du and P.M. Pardalos (eds.): Handbook of Combinatorial Optimization (vol. 2), Kluwer Academic Publishers. Boston, 1998; 331-395. P.P. Perny and B. Roy: "The use of fuzzy outranking relations in preference modelling," Fuzzy Sets and Systems 49:33-53 (1992). A. Rosenfeld: "Fuzzy graphs," In: L.A. Zadeh, K.S. Fu and M. Shimura (Eds.): Fuzzy sets and their applications to cognitive and decision processes, Academic Press, New York, 1975; 77-95. E.H. Ruspini: "A new approach to clustering," Information and Control 15:22-32 (1969). J. Siskos, J. Lochard and J. Lombard: "A multicriteria decision making methodology under fuzziness: application to the evaluation of radiological protection in nuclear power plants," in H.J.Zimmermann, L.A. Zadeh and B.R. Gaines (eds.): fuzzy Sets and Decision Analysts, North Holland, Amsterdam, 1984: 261-283.
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