A hierarchical segmentation for image processing

dc.book.title2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
dc.contributor.authorZarrazola Rivera, Edwin
dc.contributor.authorMontero De Juan, Francisco Javier
dc.contributor.authorYáñez Gestoso, Francisco Javier
dc.contributor.authorGómez González, Daniel
dc.date.accessioned2023-06-20T05:44:18Z
dc.date.available2023-06-20T05:44:18Z
dc.date.issued2010
dc.description.abstractSegmentation algorithms are well known in the field of image processing. In this work we propose an efficient and polynomial algorithm for image segmentation based on fuzzy set theory. The main difference with the classical segmentation algorithms is in the output given by the segmentation process. Since the classical output for segmentation algorithms give us the homogeneous regions in the image, our proposal is to produce an hierarchical information (in a similar way as a dendrogam does in classical clustering methods) of how the groups are formed in the image, from the initial situation in which all pixels are in the same group to the final situation in which the whole image is divided in the minimal information units.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/16036
dc.identifier.isbn978-1-4244-8126-2
dc.identifier.officialurlhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5586420
dc.identifier.relatedurlhttp://www.ieee.org
dc.identifier.urihttps://hdl.handle.net/20.500.14352/45334
dc.language.isoeng
dc.page.final4
dc.page.initial1
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Conference Publications
dc.relation.projectIDTIN2009-07901
dc.rights.accessRightsrestricted access
dc.subject.cdu510.64
dc.subject.keywordFuzzy set theory
dc.subject.keywordImage segmentation
dc.subject.keywordPattern clustering
dc.subject.keywordPolynomials
dc.subject.ucmLógica simbólica y matemática (Matemáticas)
dc.subject.unesco1102.14 Lógica Simbólica
dc.titleA hierarchical segmentation for image processingen
dc.typebook part
dcterms.referencesH. Bustince, J. Fernández, R. Mesiar and J. Montero: "Overlap functions." Submitted. D. Dubois and H. Prade: Fuzzy sets and Systems, Theory and Applications (Academic Press, Orlando, Florida, 1997). Dubois, H. Prade: "Ranking fuzzy numbers in the setting of possibility theory." Information Sciences 30, 183-224 (1983). A. del Amo, J. Montero, G. Biging and V. Cutello, "Fuzzy classification systems." European Journal of Operational Research 156, 459-507 (2004). A. del Amo, J. Montero, A. Fernández, M. López, J. Tordesillas and G. Biging: "Spectral fuzzy classification: an application." IEEE Transactions on Systems Man and Cybernetics (C) 32, 42-48 (2002). M. Ester, R. Ge, B. J. Gao, Z. Hu, B. Ben-Moshe Joint Cluster Analysis of Attribute Data and Relationship Data: the Connected k-Center Problem. ACM Transactions on Knowledge Discovery from Data (TKDD) Halkidi M., Batistakis Y., Vazirgiannis M.: On Clustering Validation Techniques. Journal of Intelligent Systems 17, 107-145 (2001). G. Facchinetti, R.G. Ricci: A characterization of a general class of ranking functions on triangular fuzzy numbers. Fuzzy Sets and Systems 146, 297-312 (2004). D. Gómez and J. Montero, "A discussion on aggregation operators." Kybernetika 40, 107-120 (2004). D. Gómez, J. Montero and J. Yáñez: "A coloring algorithm for image classification." Information Sciences 176, 3645-3657 (2006). D. Gómez, J. Montero, J. Yáñez and C. Poidomani, "A graph coloring algorithm approach for image segmentation". Omega 35, 173-183, 2007. (Pubitemid 44317623) O. Kabva and S. Seikkala: "On fuzzy metric spaces." Fuzzy Sets and Systems 12, 215-229 (1984). A. Kaufman, M. Gupta: Introduction to Fuzzy Arithmetic (Van Nostrand Reinhold, New York, 1985). J. Montero, D. Gómez and H. Bustince, "On the relevance of some families of fuzzy sets. " Fuzzy Sets and Systems 158, 2429-2442 (2007). J. Montero, V. López and D. Gómez, "The role of fuzziness in decision making." In: D. Ruan et al., Fuzzy Logic: an spectrum of applied and theoretical issues, pp. 337-349 (Springer, Berlin, 2007). S. Muñoz, M.T. Ortuño, J. Ramírez, J. Yáñez: "Coloring fuzzy graphs." Omega 33, 211-221 (2005). M. Nachtegael, T. Mlange and E.E. Kerre, "The possibilities of fuzzy logic in image processing." Lecture Notes in Computer Science 4815, 198-208 (2007). 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, pp. 331-395 (Kluwer Academic Publishers, Boston, 1998). X. Wang and E.E. Kerre: "Reasonable properties for the ordering of fuzzy quantities (I)." Fuzzy Sets and Systems 118, 375-385 (2001). S. Wasserman, and K. Faust (1994). " Social Networks Analysis". Cambridge University Press. J. Yáñez, S. Muñoz and J. Montero: "Graph coloring inconsistencies in image segmentation." Computer Engineering and Information Sciences 1, 435-440 (2008). L.A. Zadeh: "Fuzzy sets." Information and Control 8, 338-353 (1965).
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