基于素描语义信息和超像素合并的图像分割

基于素描语义信息和超像素合并的图像分割

ID:33990869

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页数:58页

时间:2019-03-03

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1、万方数据AbstractImagesegmentationisafundamentalandchallengingresearchprobleminimageprocessingfield.Researchonsegmentationmethodshouldcombineboththecharacteristicsoftheimagedataitselfandthesubsequentapplicationofdividingresult.Inimagescontainingtargetwhichhasthefeatur

2、ethatthebodymarkingshavetwodifferentcolorsalternatelyrepeated,likezebrasandtigers,tosplitupthetargetasawholeisdifficult.Basedonthevisualcomputingtheory,thispapergetsthesketchmapusingtheinitialsketchmodel.Sketchsegmentscharacterizethepositionanddirectionofthesingu

3、larityintheimage.Inimageswearedealingwith,singularityinformationfallsintotwocategories,namely,traditionalboundariesandthebordersbetweenbandsandstripes.Inimagesegmentationfiled,thetraditionalboundariesshouldbereservedasthefinalsegmentboundaries,whiletheboundarybet

4、weenthebandsandstripesisduetodifferenceincolorofadjacentbands.Becauseoftheregularityinbandsandstripesofzebraandtiger,inthefinalsegmentationresult,differentwithtraditionalboundaries,boundarybetweenthebandscannotbethefinalsegmentationboundaries,soastosegmentthetarg

5、etasawhole.Therefore,thispaperbuildsgeometricblockswiththesegmentsthatcomposethesketchmapandthenmapsthegeometricblockstothecorrespondingpositionsoftheoriginalimageandextractstheco-occurrencematrixbasedonthegeometricblocks.Wetreattheco-occurrencematrixasthefeature

6、softhecorrespondinglinesandthendividethesketchsegmentsintobandandstripescategoryandgeneralboundarymarkingscategorybasedonthefeatures.Forthesuperpixelsgotfromtheover-segmentationmethod,wemergethemundertheguidanceofthesketch-classification-basedsemanticinformation.

7、Forthesuperpixelswhichbeguidedbythebandandstripescategory,wecountupthegrayvaluesofthemandthenmakeafurthersegmentationbasedonthegrayscalestatisticssymbioticrelationshipbetweeneachsuperpixelanditsneighbors.Thus,wegetthefinalsegmentationresult.Simulationresultsshowt

8、hattheproposedmethodcangetbettersegmentationresults.Thispaperalsoappliestheproposedmethodtothecolorimagesegmentation.Comparedwiththegray-scaleimage,thecolorima

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