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基于尺度不变特征变换的车牌特征提取及BBF匹配方法（英文）.docx

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基于尺度不变特征变换的车牌特征提取及BBF匹配方法（英文） Title:VehicleLicensePlateFeatureExtractionandBBFMatchingMethodBasedonScale-InvariantFeatureTransform Abstract: Licenseplaterecognitionplaysavitalroleinintelligenttransportationsystemsandlawenforcement.Thispaperproposesamethodforvehiclelicenseplatefeatureextractionandmatchingbasedonthescale-invariantfeaturetransform(SIFT)algorithm.SIFTisarobustandreliablefeatureextractiontechniquethatcanhandlevariationsinscale,rotation,andviewpoint.Byutilizingthedistinctivefeaturesoflicenseplates,accurateandefficientmatchingcanbeachieved. 1.Introduction: Licenseplaterecognitionhasgainedimmenseimportanceinthefieldofintelligenttransportationsystems.Theaccurateextractionandmatchingoflicenseplatefeaturesplayasignificantroleinvariousapplications,includingtrafficanalysis,tollcollection,andvehicleidentification.Inthispaper,wepresentamethodthatutilizestheSIFTalgorithm,awell-establishedfeatureextractiontechnique,toachieverobustandreliablelicenseplatefeatureextractionandmatching. 2.LiteratureReview: Severalapproacheshavebeenproposedforlicenseplaterecognition,buttheperformanceandaccuracyvaryindifferentscenarios.FeatureextractiontechniquessuchasSIFT,SURF,andORBhavebeenwidelyemployedduetotheirrobustnessagainstscaleandrotationchanges.However,theSIFTalgorithmhasshownsuperiorperformanceinvariousapplications,includingobjectrecognitionandimagematching. 3.Methodology: a.LicensePlateLocalization:First,thelicenseplateregionislocalizedusingimageprocessingtechniquessuchasedgedetection,thresholding,andmorphologicaloperations.Thelocalizedregionisthensegmentedintoindividualcharactersusingtechniqueslikeconnectedcomponentanalysis. b.FeatureExtraction:SIFTisappliedtoextractrobustanddistinctivefeaturesfromeachlicenseplatecharacter.TheSIFTalgorithmdetectskeypointsinthelicenseplatecharactersandcomputestheirdescriptors. c.FeatureMatching:Theextractedfeaturesarecomparedusingthebrute-forcematching(BBF)algorithm.BBFsearchesforthenearestneighbormatchbetweenthequeryimageandthedatabaseimageus