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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
2023 Impact Factor: 1.1
2023 SCImago Journal Rankings: 0.331
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 (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/1.601932-
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
dc.identifier.issnl0091-3286-

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