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1、InternationalJournalofSoftComputingandEngineering(IJSCE)ISSN:2231-2307,Volume-2,Issue-6,January2013SurveyonImageSegmentationUsingGraphBasedMethodsNalina.P,Muthukannan.KTheworkofShiandMalik,1997[9];PresentsAbstract—ThemaingoalofthispaperistosurveythehighSegmentationbasedoneigenvector-b
2、asedmethodsthesequalityofimagesegmentationwithimprovedspeedandstability.methodsaretooslowtobepracticalformanyapplications.InInthispapertosegmenttheimageusingthreedifferentgraphRatanetal.(1999)[11],methoddescribedinthispaperhasbasedsegmentationalgorithms.TheseareIsoperimetricbeenusedin
3、large-scaleimagedatabaseapplications.ItisfailSegmentationNormalisdCutSegmentation,andSpectraltocaptureperceptuallyimportantnon-localpropertiesofanSegmentation.Applythesealgorithmsintheimageandfindoutimage.TheWorkofUrquhart,1982;Zahn,1971[12&13]segmentationresult.Usingthesegmentationre
4、sultstheperformancewillbeanalyzedwithspeedandstability.ToPresentsSegmentationBasedonEarlygraph-basedmethods.determinestabilityofimagebyaddingtheAdditiveNoise,MaindisadvantageisFixedthreshold&LocalMeasuresinMultiplicativeNoise,ShotNoiseComputation.PedroF.FelzenszwalbandDanielP.Huttenlo
5、cher,2004[1]itworksBasedKrusal’sAlgorithamKeywords—Isoperimetric,NormalizedCut,PerformancedrawbackofthispaperisLowVariabilityimageregionsEvaluation,Spectral,Segmentation.whileignoringdetailinHighvariabilityregions..ItisverydifficultforuserstochooseanappropriatevalueforanI.INTRODUCTION
6、expectedsegmentedsize.OnereasonforthisinterestisthatA.GeneralIntroductionthesegmentationqualityofNcutsandothergraph-basedsegmentationmethods[2]isverygood.TheEveryimageisasetofpixelandpartitioningthosepixelsrecently-developedisoperimetricmethodofgraphonthebasisofthesimilarcharacteristi
7、cs.segmentationispartitioning[3]hasdemonstratedthatqualitypartitionsofadividinganimageintosubpartitionsonthebasisofsomegraphmaybedeterminedquicklyandthatthepartitionsaresimilarcharacteristicslikecolor,intensityandtextureisstablewithrespecttosmallchangesinthegraph(mask).calledimagesegm
8、entat
