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Conference Paper: Image segmentation towards natural clusters

TitleImage segmentation towards natural clusters
Authors
Issue Date2008
PublisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000545
Citation
The 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, FL., 8-11 December 2008. In International Conference on Pattern Recognition, 2008, p. 1-4 How to Cite?
AbstractTo find how many clusters in a sample set is an old yet unsolved problem in unsupervised clustering. Many segmentation methods require the user to specify the number of regions in the image or some delicate thresholds to get a sensible segmentation. In this paper, we propose a segmentation method that is able to automatically determine the number of regions in an image. The method effectively discerns distinct regions by analyzing the properties of the joint boundary between neighboring regions. By requiring that every region should be distinct from each other, it is able to choose a natural partition from the partition set which contains all possible partitions. Results are given at the end of this paper to demonstrate the effectiveness of this approach. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/62146
ISBN
ISSN
2023 SCImago Journal Rankings: 0.584
References

 

DC FieldValueLanguage
dc.contributor.authorTan, Zen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-07-13T03:54:49Z-
dc.date.available2010-07-13T03:54:49Z-
dc.date.issued2008en_HK
dc.identifier.citationThe 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, FL., 8-11 December 2008. In International Conference on Pattern Recognition, 2008, p. 1-4en_HK
dc.identifier.isbn978-1-4244-2175-6-
dc.identifier.issn1051-4651en_HK
dc.identifier.urihttp://hdl.handle.net/10722/62146-
dc.description.abstractTo find how many clusters in a sample set is an old yet unsolved problem in unsupervised clustering. Many segmentation methods require the user to specify the number of regions in the image or some delicate thresholds to get a sensible segmentation. In this paper, we propose a segmentation method that is able to automatically determine the number of regions in an image. The method effectively discerns distinct regions by analyzing the properties of the joint boundary between neighboring regions. By requiring that every region should be distinct from each other, it is able to choose a natural partition from the partition set which contains all possible partitions. Results are given at the end of this paper to demonstrate the effectiveness of this approach. © 2008 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000545en_HK
dc.relation.ispartofInternational Conference on Pattern Recognitionen_HK
dc.rights©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.titleImage segmentation towards natural clustersen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailYung, NHC: nyung@hkucc.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICPR.2008.4761576-
dc.identifier.scopuseid_2-s2.0-77957934683en_HK
dc.identifier.hkuros164706en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77957934683&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1-
dc.identifier.epage4-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK
dc.identifier.scopusauthoridTan, Z=26427814600en_HK
dc.customcontrol.immutablesml 140725-
dc.identifier.issnl1051-4651-

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