外文文献及译文.docx

外文文献及译文.docx

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外文文献及译文

本科毕业设计

外文文献及译文

文献、资料题目：

FoodHandlingUsingComputer

文献、资料来源：

文献、资料发表（出版）日期：

2008.12

院（部）：

机电工程学院

专业：

机械工程及自动化

班级：

机械054

姓名：

刘翠芹

学号：

2005071222

指导教师：

董明晓教授

翻译日期：

2009.5.15

外文文献：

FoodHandlingandPackagingusingComputervisionandRobot

Abstract

Eventhoughtheuseofrobotvisionsysteminmanufacturingsectorsisnowacommonplace,however,thetechnologyembodiedinthesedevicesispoorlymatchedtoindustrialneedsoffoodprocessors.Inparticular,foodprocessingimposesspecialdemandsuponmachinery.Forinstancethevisionsensormustbeprogrammedtodetectthepositionofsingleandisolatedobjectaswellasoverlappingoroccludingobjects.Specialgrippershavetobedesignedforhandlingoffoodarticlessuchthattheyhaveminimumcontactwiththefooditemsandhencecausingminimumdamagetothem.Inthisproject,startedoverayearago,avisionguidancesystemisbeingdevelopedtomeetthisobjective.ThesystemintegratesthemodifiedversionoftheHoughtransformalgorithmasthemainrecognitionengine.Themethodsandproceduresweretestedoncommerciallyproducedbeefburgers.

1.Introduction

Fromtheincomingdowntothepackaginglines,locating,recognizingandhandlingfoodobjectsareveryimportantinfoodprocessingindustry.Thesetasksareperformedroutinelyinfoodindustrymainlyforqualityevaluationandproductclassification.Suchtasksareverylaboriouslydemandingandtendtorelyheavilyonroleofthehumanoperator[1].Handsofworkersusingrawmaterialsofanimalorigincanheavilybecontaminatedwithfaecalandothermicro-pathogenicorganisms[2].ThestudybyTrickett[3]hasshownastronglinkbetweenfoodpoisoningandthehygienestandardsoffoodprocessors.Completeautomationoffoodhandlingandpackagingbymeansofroboticarmisthemosteffectivemeanstoeliminateinfluenceofmanualhandlingofmicrobiologicalqualityoffoods.

Robotshavesuccessfullybeenappliedinawiderangeoffoodindustriesprimarilydealingwithwell-definedprocessesandproductsnotonlybecausetheyarerelativelycleanandhygienic,alsobecauseoftheirflexibility,ruggednessandrepeatability.ThistrendwillcontinuetogrowwiththeincreasingscrutinyandregulatoryenforcementssuchasandHazardAnalysisandCriticalControlPoints（HACCP）togetherwithcompaniesthatarelookingforwaystodecreaseoreliminateworkerexposuretorepetitivemotiontasksandharshenvironment.Howeverthereareproblemsandchallengesassociatedwiththeuseofrobotsinfoodindustry[4].

Firstlythefoodproducts,despiteofthesametype,differinsize,shapeandotherphysicalvariables.Thisimposesspecialdemandsformachinerytohandlethem,requiringmultiplesensory,manipulationandenvironmentalcapabilitiesbeyondthoseavailableinrobotsdesignedtoautomatemanufacturingtasks.Secondlythesuccessofapplyingrobotsforfoodhandlers,hingesuponthesuccessofdetecting,locating,recognizingandhandlingseverelyoverlappingandoccludingcasesofsimilarfoodobjects.Thirdly,foodobjectsareoftendelicateandusuallycoveredwitheitherslipperyorviscoussubstances,makinghighspeedhandlingofsuchtargetsaverychallengingtask.Theexistingcontact-basedmechanismssuchasthevacuumsuctioningandtheclampgrippingarenotapplicablebecausetheycanpotentiallycauseinjuriesandbruisingtofoodproducts.Hencefurtherresearchisneededinordertosolvetheseproblems.Thispaperaddressessomeoftheproblems,focusingonthemethodsusedtocontroltherobotdirectlyfromthevisionsensor,attemptingtosimulatethewaythathumansusetheireyestonaturallycontrolthemotionoftheirarms.

2.MaterialsandMethods

2.1SamplePreparation

Thechosenfoodforthisstudyisalocallyproducedbeef-burger.Itpossessesalltheimportantcharacteristicswhichareuniquetofoodproducts,suchthattheyareveryfragileandeasilydeformed.Theaveragesizeofthebeef-burgersis8.5mminthicknessand46.1mmradiusand69.3gminweight.Surfaceimagesoftestsampleswereacquiredusing8-bitrobotvisionsystemwithuniformwhitebackground.Thewhitebackgroundprovidesexcellentcontrastbetweentheburgerandthebackground.Thechosenexposurewasadjustedsothattheimageintensityhistogramswereapproximatelycenteredatmid-wayofthefull-scalerange.Thefocaldistancewasselectedtoallowsingleaswellasmultiplesamplestofitintheimageframe.

2.2Robotvision

TherobotvisionsystemsusedinthisstudyistheAdeptCobra6004-DOFarticulatedscararobot,manufacturedbyAdeptTech.,USAandequippedwithAdeptVisionInterface,MV-5AdeptcontrollerandTM1001CCDmonochromecameramanufacturedbyPulnixInc.,Canada.Thecamerawasmountedontolink2ofrobotarmandilluminatedusingthewarmwhitedeluxe（WWX）fluorescentlighting.ThecameraisfittedwithaC-mountadaptertopermittheuseofTamronf/25.58-mmlens.TheTM1001cameraisconnectedtotheAVIcardviaa12-pinHirosetypecameraconnectorofHiroseInc.,Japan.TherobotvisionsystemwasoperatedusingAdept’sAIMSv4.0andprogramminglibraries,runningon1.7GHzand255MBRAMPentiumIVPC.Figure1showstheset-upofrobotvisionsystem.

2.3ImageProcessing

Theobjectiveofimageprocessinginrobotvisionapplicationsismainlytoextractmeaningfulandaccurateinformationfromtheimages,endowingtherobotswithmoresophisticatedpositioncontrolcapabilitiesthroughtheuseofvisionfeedback.Theuseofasimplegeometricmethodsuchasintroducingspeciallydesignedcuesintotheimagescenewillnotworkinthisapplicationsincetheburgerimagesaregenerallycomplex,difficulttomodelandpartiallyorextensivelyoccludeddependingontheviewingangle.Figure2showsthetypicalbeef-burgerimage.

Inordertoaccuratelytranslateburgerpositionstorobotmovements,theformergeometricfeaturesmustfirstlybeextractedandsecondlymatchedtotherobot'sworkspace.Inthisapplicationoneoftheusefulfeatureswhichuniquelycharacterizetheposeofaburgerinarbitrarylocationsisitscentroid.Thisgeometricdescriptorisapplicablesincetheshapeofaburgerisapproximatelycircular.Furthermorethisfeaturepreservesvariancetotranslation,rotationandscaling.Beforecomputingthecentroidoftherealburgerimages,severalpreprocessingoperationsneedtobeperformedoneachimage.

Edgedetectionoperationiscarriedouttodetectthecontouroftheconnectedandisolatedcomponents,thereby,effectivelytransformingtheoriginaldataintoaformsuitableforfurtherprocessing.TheedgeresultsofFigure2computedusingwell-knownSobelandRobertoperators[5]areshowninFigures3（a）,（b）,（c）&（d）.Fromthesefiguresitcanbeseenthattheedgesdeterminedbytheseoperatorscomprisedofmanyfalseedges,discontinuitiesandspuriousspotsresultingfromunevenandirregularsurfaceoftheburger,non-uniformlightreflectionandshadows.Thesedrawbacksarenotacceptableforapplicationdescribedinthispaper.

Amoresophisticatedmethodisneededinordertoobtainacceptableresults.ThemethodusedtosolvetheseproblemswasbasedonCannyedgedetectionoperator[6].Interestedreadersarereferredtothispublicationfordetailedmathematicalexplanationofthisrelativelynewedgedetector.Hereonlytheimportantprinciplesarepresentedinordertofacilitatediscussiononrobotvisionapplicationsonfoodhandling.Cannymethodforedgedetectionisprincipallybasedonsomegeneralideas.

FirstlyCannywasthefirsttodemonstratethatconvolvinganimagewithasymmetric2-DGaussianfilterandthen,secondly,differentiatinginthedirectionofthegradientformtheedgemagnitudeimage.Thepresenceofedgesintheoriginalimagegivesrisetoridgesingradientmagnitudeimage.Theobjectiveistodetectthetrueedgeintherightplace.Thiscanbedoneusingmethodknownasnon-maximalsuppressiontechnique.Essentiallythismethodworksbytrackingalongthetopoftheridges,retainingonlythosepointsatthetopoftheridge,whilstsuppressingallothers.Thetrackingprocessexhibitshysteresiscontrolledbytwoimportantparameters.TheyarethelowerthresholdvalueTlow,andtheupperthresholdvalueThigh.IftheedgeresponseisaboveThigh,thenthispixeldefinitelyconstitutesanedgeandhenceretained.PixelslessthanThighbutgreaterthangreaterTlowareconsideredasweakedges.Finallytrackingwasdonetobridgealldiscontinuededgesaswellastoeliminatethefalseones.Weakedgesareretainedonlyiftheyareconnectedtothestrongedge.Theresultoftheseoperationsisanimagewiththinlinesofedgepointswithimprovededge-to-noiseratio.Eventhoughthismethodreducestheeffectofnoise,however,theoverallqualityofedgesdependslargelyontheoptimalselectionofthestandarddeviationı.whichdefinestheGaussianmaskforCanny’sedgedetection.Experimentallytheoptimumvaluewassetto3.Thiscorrespondstoa25X25kernel.Thisvalueisfixedforgivensetofbackgroundilluminationandimagegain.Changeinanyoftheseexternalfactorssuchasillumination,imagegain,backgroundcolourwillalsoaffecttheoptimumvalueofı.Figures4（a）&（b）showresultsforcannyedgedetectionwithısetto1and3.

ComparingFigure3andFigure4,itcanbeseenclearlythattheedgesdeterminedbyCanny'soperatorarelesscorruptedcomparedtoedgesdetectedeitherbySobelorRobertoperator.TheburgeredgesaremorecompleteinFigure4whereasinFigure3theyareonlypartiallyvisibleandmoreobscured.FurthermoretheretentionofmajordetailbytheCannyoperatorisveryevident.Thepresenceofoverlappingandpartiallyocclud