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0湖南科技大学智能控制理论论文姓名：_____________学院：_____________班级：_____________学号：_____________1LicensePlateRecognitionBasedOnPriorKnowledgeAbstractInthispaper,anewalgorithmbasedonimprovedBP(backpropagation)neuralnetworkforChinesevehiclelicenseplaterecognition(LPR)isdescribed.Theproposedapproachprovidesasolutionforthevehiclelicenseplates(VLP)whichweredegradedseverely.Whatitremarkablydiffersfromthetraditionalmethodsistheapplicationofpriorknowledgeoflicenseplatetotheprocedureoflocation,segmentationandrecognition.Colorcollocationisusedtolocatethelicenseplateintheimage.Dimensionsofeachcharacterareconstant,whichisusedtosegmentthecharacterofVLPs.TheLayoutoftheChineseVLPisanimportantfeature,whichisusedtoconstructaclassifierforrecognizing.TheexperimentalresultsshowthattheimprovedalgorithmiseffectiveundertheconditionthatthelicenseplatesweredegradedseverelyVehicleLicense-Plate(VLP)recognitionisaveryinterestingbutdifficultproblem.Itisimportantinanumberofapplicationssuchasweight-and-speed-limit,redtrafficinfringement,roadsurveysandparksecurity[1].VLPrecognitionsystemconsistsoftheplatelocation,thecharacterssegmentation,andthecharactersrecognition.Thesetasksbecomemoresophisticatedwhendealingwithplateimagestakeninvariousinclinedanglesorundervariouslighting,weatherconditionandcleanlinessoftheplate.Becausethisproblemisusuallyusedinreal-timesystems,itrequiresnotonlyaccuracybutalsofastprocessing.MostexistingVLPrecognitionmethods[2],[3],[4],[5]reducethecomplexityandincreasetherecognitionratebyusingsomespecificfeaturesoflocalVLPsandestablishingsomeconstrainsontheposition,distancefromthecameratovehicles,andtheinclinedangles.Inaddition,neuralnetworkwasusedtoincreasetherecognitionrate[6],[7]butthetraditionalrecognitionmethodsseldomconsiderthepriorknowledgeofthelocalVLPs.Inthispaper,weproposedanewimprovedlearningmethodofBPalgorithmbasedonspecificfeaturesofChineseVLPs.TheproposedalgorithmovercomesthelowspeedconvergenceofBPneuralnetwork[8]andremarkableincreasestherecognitionrate2especiallyundertheconditionthatthelicenseplateimagesweredegradeseverely.IndexTerms-Licenseplaterecognition,priorknowledge,vehiclelicenseplates,neuralnetwork.31.NeuralNetworkIntroduction①ObjectiveAsyoureadthesewordsyouareusingacomplexbiologicalneuralnetwork.Youhaveahighlyinterconnectedsetofsome1011neuronstofacilitateyourreading,breathing,motionandthinking.Eachofyourbiologicalneurons，arichassemblyoftissueandchemistry,hasthecomplexity,ifnotthespeed,ofamicroprocessor.Someofyourneuralstructurewaswithyouatbirth.Otherpartshavebeenestablishedbyexperience.Scientistshaveonlyjustbeguntounderstandhowbiologicalneuralnetworksoperate.Itisgenerallyunderstoodthatallbiologicalneuralfunctions,includingmemory,arestoredintheneuronsandintheconnectionsbetweenthem.Learningisviewedastheestablishmentofnewconnectionsbetweenneuronsorthemodificationofexistingconnections.Thisleadstothefollowingquestion:Althoughwehaveonlyarudimentaryunderstandingofbiologicalneuralnetworks,isitpossibletoconstructasmallsetofsimpleartificial“neurons”andperhapstrainthemtoserveausefulfunction?Theansweris“yes.”Thisbook,then,isaboutartificialneuralnetworks.Theneuronsthatweconsiderherearenotbiological.Theyareextremelysimpleabstractionsofbiologicalneurons,realizedaselementsinaprogramorperhapsascircuitsmadeofsilicon.Networksoftheseartificialneuronsdonothaveafractionofthepowerofthehumanbrain,buttheycanbetrainedtoperformusefulfunctions.Thisbookisaboutsuchneurons,thenetworksthatcontainthemandtheirtraining.②HistoryThehistoryofartificialneuralnetworksisfilledwithcolorful,creativeindividualsfrommanydifferentfields,manyofwhomstruggledfordecadestodevelopconceptsthatwenowtakeforgranted.Thishistoryhasbeendocumentedbyvariousauthors.OneparticularlyinterestingbookisNeurocomputing:FoundationsofResearchbyJohnAndersonandEdwardRosenfeld.Theyhavecollectedandeditedasetofsome43papersofspecialhistoricalinterest.Eachpaperisprecededbyan4introductionthatputsthepaperinhistoricalperspective.Historiesofsomeofthemainneuralnetworkcontributorsareincludedatthebeginningofvariouschaptersthroughoutthistextandwillnotberepeatedhere.However,itseemsappropriatetogiveabriefoverview,asampleofthemajordevelopments.Atleasttwoingredientsarenecessaryfortheadvancementofatechnology:conceptandimplementation.First,onemusthaveaconcept,awayofthinkingaboutatopic,someviewofitthatgivesclaritynottherebefore.Thismayinvolveasimpleidea,oritmaybemorespecificandincludeamathematicaldescription.Toillustratethispoint,considerthehistoryoftheheart.Itwasthoughttobe,atvarioustimes,thecenterofthesoulorasourceofheat.Inthe17thcenturymedicalpractitionersfinallybegantoviewtheheartasapump,andtheydesignedexperimentstostudyitspumpingaction.Theseexperimentsrevolutionizedourviewofthecirculatorysystem.Withoutthepumpconcept,anunderstandingoftheheartwasoutofgrasp.Conceptsandtheiraccompanyingmathematicsarenotsufficientforatechnologytomatureunlessthereissomewaytoimplementthesystem.Forinstance,themathematicsnecessaryforthereconstructionofimagesfromcomputer-aidedtopography(CAT)scanswasknownmanyyearsbeforetheavailab