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1、Tutorial:ImageSegmentationYu-HsiangWang(王昱翔)E-mail:r98942059@ntu.edu.twGraduateInstituteofCommunicationEngineeringNationalTaiwanUniversity,Taipei,Taiwan,ROCAbstractForsomeapplications,suchasimagerecognitionorcompression,wecannotprocessthewholeimagedirectlyforthereasonthati
2、tisinefficientandunpractical.Therefore,severalimagesegmentationalgorithmswereproposedtosegmentanim-agebeforerecognitionorcompression.Imagesegmentationistoclassifyorclusteranimageintoseveralparts(regions)accordingtothefeatureofimage,forexample,thepixelvalueorthefrequencyres
3、ponse.Uptonow,lotsofimagesegmentationalgo-rithmsexistandbeextensivelyappliedinscienceanddailylife.Accordingtotheirsegmentationmethod,wecanapproximatelycategorizethemintoregion-basedseg-mentation,dataclustering,andedge-basesegmentation.Inthistutorial,wesurveyseveralpopulari
4、magesegmentationalgorithms,discusstheirspecialties,andshowtheirsegmentationresults.Moreover,somesegmentationapplicationsaredescribedintheend.1.IntroductionImagesegmentationisusefulinmanyapplications.Itcanidentifytheregionsofinterestinasceneorannotatethedata.Wecategorizethe
5、existingsegmentationalgo-rithmintoregion-basedsegmentation,dataclustering,andedge-basesegmentation.Region-basedsegmentationincludestheseededandunseededregiongrowingalgo-rithms,theJSEG,andthefastscanningalgorithm.Allofthemexpandeachregionpixelbypixelbasedontheirpixelvalueor
6、quantizedvaluesothateachclusterhashighpositionalrelation.Fordataclustering,theconceptofthemisbasedonthewholeimageandconsidersthedistancebetweeneachdata.Thecharacteristicofdataclus-teringisthateachpixelofaclusterdoesnotcertainlyconnective.Thebasismethodofdataclusteringcanbe
7、dividedintohierarchicalandpartitionalclustering.Furthermore,weshowtheextensionofdataclusteringcalledmeanshiftalgorithm,althoughthisalgorithmmuchbelongingtodensityestimation.Thelastclassificationofsegmenta-tionisedge-basedsegmentation.Thistypeofthesegmentationsgenerallyappl
8、ies1edgedetectionortheconceptofedge.Thetypicaloneisthewatershedalgorithm,butitalwayshasth
