File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Segmentation of color images based on the gravitational clustering concept

TitleSegmentation of color images based on the gravitational clustering concept
Authors
KeywordsBoundaries
Clustering
Force effective function
Gravitational clustering
Image segmentation
Markovian model
Objective evaluation
RGB color space
Segmented regions
Issue Date1998
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe
Citation
Optical Engineering, 1998, v. 37 n. 3, p. 989-1000 How to Cite?
AbstractA new clustering algorithm derived from the Markovian model of the gravitational clustering concept is proposed that works in the RGB measurement space for color image. To enable the model to be applicable in image segmentation, the new algorithm imposes a clustering constraint at each clustering iteration to control and determine the formation of multiple clusters. Using such constraint to limit the attraction between clusters, a termination condition can be easily defined. The new clustering algorithm is evaluated objectively and subjectively on three different images against the K-means clustering algorithm, the recursive histogram clustering algorithm for color (also known as the multi-spectral thresholding), the Hedley-Yan algorithm, and the widely used seed-based region growing algorithm. From the evaluation, it is observed that the new algorithm exhibits the following characteristics: (1) its objective measurement figures are comparable with the best in this group of segmentation algorithms; (2) it generates smoother region boundaries; (3) the segmented boundaries align closely with the original boundaries; and (4) it forms a meaningful number of segmented regions. © 1998 Society of Photo-Optical Instrumentation Engineers.
Persistent Identifierhttp://hdl.handle.net/10722/42776
ISSN
2015 Impact Factor: 0.984
2015 SCImago Journal Rankings: 0.485
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYung, HCen_HK
dc.contributor.authorLai, HSen_HK
dc.date.accessioned2007-03-23T04:31:58Z-
dc.date.available2007-03-23T04:31:58Z-
dc.date.issued1998en_HK
dc.identifier.citationOptical Engineering, 1998, v. 37 n. 3, p. 989-1000en_HK
dc.identifier.issn0091-3286en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42776-
dc.description.abstractA new clustering algorithm derived from the Markovian model of the gravitational clustering concept is proposed that works in the RGB measurement space for color image. To enable the model to be applicable in image segmentation, the new algorithm imposes a clustering constraint at each clustering iteration to control and determine the formation of multiple clusters. Using such constraint to limit the attraction between clusters, a termination condition can be easily defined. The new clustering algorithm is evaluated objectively and subjectively on three different images against the K-means clustering algorithm, the recursive histogram clustering algorithm for color (also known as the multi-spectral thresholding), the Hedley-Yan algorithm, and the widely used seed-based region growing algorithm. From the evaluation, it is observed that the new algorithm exhibits the following characteristics: (1) its objective measurement figures are comparable with the best in this group of segmentation algorithms; (2) it generates smoother region boundaries; (3) the segmented boundaries align closely with the original boundaries; and (4) it forms a meaningful number of segmented regions. © 1998 Society of Photo-Optical Instrumentation Engineers.en_HK
dc.format.extent1501466 bytes-
dc.format.extent5183 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oeen_HK
dc.relation.ispartofOptical Engineeringen_HK
dc.rightsCopyright 1998 Society of Photo-Optical Instrumentation Engineers. This paper was published in Optical Engineering, 1998, v. 37 n. 3, p. 989-1000 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBoundariesen_HK
dc.subjectClusteringen_HK
dc.subjectForce effective functionen_HK
dc.subjectGravitational clusteringen_HK
dc.subjectImage segmentationen_HK
dc.subjectMarkovian modelen_HK
dc.subjectObjective evaluationen_HK
dc.subjectRGB color spaceen_HK
dc.subjectSegmented regionsen_HK
dc.titleSegmentation of color images based on the gravitational clustering concepten_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=37&issue=3&spage=989&epage=1000&date=1998&atitle=Segmentation+of+color+images+based+on+the+gravitational+clustering+concepten_HK
dc.identifier.emailYung, HC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, HC=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.601932en_HK
dc.identifier.scopuseid_2-s2.0-0001046575en_HK
dc.identifier.hkuros36896-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0001046575&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume37en_HK
dc.identifier.issue3en_HK
dc.identifier.spage989en_HK
dc.identifier.epage1000en_HK
dc.identifier.isiWOS:000072530200034-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYung, HC=7003473369en_HK
dc.identifier.scopusauthoridLai, HS=7201967327en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats