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基于机器视觉的路面裂缝病害多目标识别技术.docx

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基于机器视觉的路面裂缝病害多目标识别技术 Abstract: Roadsurfacedistressidentificationisanimportanttaskforroadmaintenanceandmonitoring.Oneofthemostcommontypesofdistressisthecrackingoftheroadsurface.Inrecentyears,thedevelopmentofmachinevisiontechnologyhasenabledaccurateandefficientidentificationofmultipletypesofcrackdefectsonroadsurfaces.Inthispaper,amulti-targetrecognitiontechnologyforroadsurfacecrackdefectsbasedonmachinevisionisproposed.Theproposedtechnologyuseshigh-resolutionimagesandartificialintelligencealgorithmstoidentifydifferenttypesofcrackdefectsonroadsurfaces.Thispaperprovidesanoverviewoftheproposedtechnology,includingimagepreprocessing,featureextraction,andclassificationalgorithms.Experimentsdemonstratethattheproposedtechnologycanaccuratelyandefficientlyidentifydifferenttypesofcrackdefectsontheroadsurface. Introduction: Thedeteriorationofroadsurfacesisamajorconcernfortransportationinfrastructuremanagers.Roadsurfacedistressescancauseaccidents,reducetheservicelifeofpavements,andincreasethemaintenancecosts.Currently,manualinspectionmethodsareusedtodetectroadsurfacedistresses,whicharetime-consuming,labor-intensive,andhavelowaccuracy.Therefore,automatedidentificationofroadsurfacedistressesusingmachinevisiontechnologyhasbecomeapromisingapproachforroadmonitoringandmaintenance. Roadsurfacecrackingisoneofthemostcommontypesofdistress.Cracksintheroadsurfacecanbecausedbyvariousfactors,suchastrafficloads,climate,andmaterialproperties.Identifyingthetypesofcrackscanhelproadmanagersmakeinformeddecisionsonhowtobestaddresstheissues.However,themanualinspectionofcrackagetypicallytakesalongtimeandhaslowaccuracy.Therefore,amachinevisionsystemthatcanaccuratelyidentifythetypeofcrackdefectcanprovidesignificantbenefitsforroadmaintenanceandmonitoring. Theproposedmulti-targetrecognitiontechnologyforroadsurfacecrackdefectsisbasedonmachinevision.Thesystemiscomposedofahigh-resolutioncamera,animageprocessingmodule,afeatureextractionmodule,andaclassificationmodule,asshowninFigure1.Thecameraisusedtocaptureimag