a novel text detectin and localization method based oncorner response

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1、ANOVELTEXTDETECTIONANDLOCALIZATIONMETHODBASEDONCORNERRESPONSELiSun,GuizhongLiu,XuemingQian,DanpingGuoSchoolofElectronicsandInformationEngineering,Xi’anJiaotongUniversity,710049,ChinaABSTRACTmethodholdtheassumptionthatbackgroundsaremuchmoresmooththantextregions.SoitispossibletoclassifytextInfo

2、rmationoftextinvideosandimagesplaysanimpor-regionandnon-textregionaccordingtoedgeortextureinten-tantroleinsemanticanalysis.Inthispaper,weproposeansity.Buthowtoreducenoisescomingfromcomplexback-effectivemethodfortextdetectionandlocalizationinnoisygroundsisstillanopenproblem.Lyuetal.proposeamet

3、hodbackground.Thealgorithmisbasedoncornerresponse.fordetectingmultilingualandmulti-resolutiontext[4].SobelComparedtonon-textregions,thereoftenexistdenseedgesedgemapsareusedasfeaturesandaspeciallocalthresholdandcornersintextregions.Sowecangetrelativelystrongisadoptedtotolocatethecandidateregio

4、noftext.Lietal.responsesfromtextregionsandlowresponsesfromnon-textproposeamethodbasedoncentralmomentsofimageblockregions.Theseresponsesprovideususefulcuesfortextde-[1].Theyprovethatdifferentscaletextcanbedetectedusingtectionandlocalizationinimages.Thenusingasimpleblockthisfeature;3)Machinelea

5、rningbasedmethodusefeaturesbasedthresholdscheme,wegetcandidateregionsfortext.extractedfromtextregionandnon-textregiontotrainsupportTheseregionsarefurtherverifiedbycombiningotherfeaturesvectormachineorneutralnetworkandthentextdetectionbe-suchascolorandsizerangeofconnectedcomponent.Finally,comes

6、asupervisedclassificationproblem.In[5],aSVMTextlineislocatedaccuratelybytheprojectionofcornerre-basedalgorithmusingresponsefromstrokefilterisproposed.sponse.TheexperimentalresultsshowtheeffectivenessofHuetal.proposeanadaptiveSVMbasedparadigm,basedourmethods.onmaximumgradientdifferencesandotherc

7、onnectedcom-IndexTerms—Textdetection,textlocalization,cornerponentfeatures,whichcanobtainrelativelylowfalserate[6].responseTheshortcomingofmachinelearningbasedmethodisthatitneedsalargenumberoftrainingsamplesofdifferentkind.Inthispaper,anewtex