A graph coloring approach for image segmentation
| dc.contributor.author | Gómez González, Daniel | |
| dc.contributor.author | Montero De Juan, Francisco Javier | |
| dc.contributor.author | Yáñez Gestoso, Francisco Javier | |
| dc.contributor.author | Poidomani, Carmelo | |
| dc.date.accessioned | 2023-06-20T09:39:24Z | |
| dc.date.available | 2023-06-20T09:39:24Z | |
| dc.date.issued | 2007 | |
| dc.description.abstract | In this paper we develop a segmentation scheme for digital images based upon an iterative binary coloring technique that takes into account changing behavior of adjacent pixels. The output is a hierarchical structure of images which allows a better understanding of complex images. In particular, we propose two algorithms that should be considered as image preprocessing techniques. | en |
| dc.description.department | Depto. de Estadística e Investigación Operativa | |
| dc.description.faculty | Fac. de Ciencias Matemáticas | |
| dc.description.refereed | TRUE | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/16612 | |
| dc.identifier.doi | 10.1016/j.omega.2005.05.003 | |
| dc.identifier.issn | 0305-0483 | |
| dc.identifier.officialurl | https//doi.org/10.1016/j.omega.2005.05.003 | |
| dc.identifier.relatedurl | http://www.sciencedirect.com/science/article/pii/S0305048305000800 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/50125 | |
| dc.issue.number | 2 | |
| dc.journal.title | OMEGA - The International Journal of Management Science | |
| dc.language.iso | eng | |
| dc.page.final | 183 | |
| dc.page.initial | 173 | |
| dc.publisher | Pergamon Elsevier Science | |
| dc.rights.accessRights | restricted access | |
| dc.subject.cdu | 517 | |
| dc.subject.keyword | Segmentation techniques | |
| dc.subject.keyword | Graph theory | |
| dc.subject.keyword | Decision support systems | |
| dc.subject.ucm | Análisis matemático | |
| dc.subject.unesco | 1202 Análisis y Análisis Funcional | |
| dc.title | A graph coloring approach for image segmentation | en |
| dc.type | journal article | |
| dc.volume.number | 35 | |
| dcterms.references | Bezdek JC. Pattern recognition with fuzzy objective function algorithms. New York: Plenum Press; 1981. Bezdek JC, Harris JD. Fuzzy partitions and relations: an axiomatic basis for clustering. Fuzzy Sets and Systems 1978;1:111–27. Foody GM. The continuum of classification fuzziness in thematics mapping. Photogrammetric Engineering and Remote Sensing 1999;65:443–51. Kerre EE, Nachtegael M. Fuzzy techniques in image processing. Heidelberg: Physica-Verlag; 2000. Pal SK, Ghosh A, Kundu MK. Soft computing for image processing. Heidelberg: Physica-Verlag; 2000. Muñoz S, Ortuño T, Ramírez J, Yáñez J. Coloring fuzzy graphs. Omega 2005;33(3):211–21. Yáñez J, Ramírez J. The robust coloring problem. European Journal of Operational Research 2003;148: 546–58. Amo A, Gómez D, Montero J, Biging G. Relevance and redundancy in fuzzy classification systems. Mathware and Soft Computing 2001;8:203–16. Amo A, Montero J, Biging G. Classifying pixels by means of fuzzy relations. International Journal of General Systems 2000;29:605–21. Amo A, Montero J, Fernández A, López M, Tordesillas J, Biging G. Spectral fuzzy classification: an application. IEEE Transactions on Systems Man and Cybernetics (C) 2002;32: 42–8. Amo A, Montero J, Biging G, Cutello V. Fuzzy classification systems. European Journal of Operational Research 2004;156:459–507. Amo A, Montero J, Cutello V. On the principles of fuzzy classification. Proceedings of the annual North American fuzzy information processing society conference (NAFIPS).1999. p. 675–79. Pardalos PM, Mavridou T, Xue J. The graph coloring problem: a bibliographic survey. In: Du DZ, Pardalos PM, editors. Handbook of combinatorial optimization, vol. 2. Boston:Kluwer Academic Publishers; 1998. p. 331–95. | |
| dspace.entity.type | Publication | |
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