外文翻译原文-基于Davinci平台的近红外成像检测系统

TheNinthInternationalConferenceonElectronicMeasurement&InstrumentsICEMI2009ANearInfraredImagingDetectionSystemBasedonDavinciPlatformLiHua,ZhangShi-chao,HanChao,ZhengMing,MengXiao-fengLiHua:Professor,DepartmentofPhysics,BeihangUniversity,Beijing,ChinaEmail:ZhangShi-chao:DepartmentofPhysics,BeihangUniversity,Beijing,ChinaEmail:AbstractInfraredimagingdetectiontechnologyisahigh-tech,involvingofoptics,electronics,machineryandcomputerscienceinmanyfields.Thetechnologynowplaysacrucialroleindetectionofearlywarning,identificationtracking,publicsecurity,firealarmandapplicationsinmanyotherfields.Thispapermainlyexpandsonanear-infraredimagingdetectionsystembasedonDavinciDigitalSignalProcessor(DSP)platform.Andthisarticledescribestheschematic,hardwarestructureandimagedataprocessingalgorithmofthenear-infraredimagingdetectionsystemindetail.Firstly,infraredradiationfromthetrackedtargetisfocusedontheCMOSnearinfraredimagesensorthroughaninfraredopticallens.TheimagesensorcontrolledbyaComplexProgrammableLogicDevice(CPLD)producesthecorrespondingimagedata,andthentheimagedataisscaledbytheCPLDtofitthefollowingdataprocessing.TheCPLDalsoplaysakeyroleinvideobufferingandnoisereduction.TheDavinciDSP-SOCwillthenacceptthedataflowafterward,andcalculatethelocationofthetargetwiththecorrespondingimageprocessingalgorithmstocontroltheservosofhorizontalandvertical,lockingandtrackingtheinfraredtargetinrealtime.TheARM9coreintheDSP-SOCisoperatedwithLinux,whichisfreeandopensource.TheusercanhumanlyprogramthecoreDSPalgorithmsandtrackingalgorithmswithaPCtogetamuchbettereffectoftracking.Withatouch-screenandTFTLCD,thesystemismuchmoreconvenientanduser-friendly.Duetothehighsensitivityandresolution,thenearinfraredimagingdetectionsystemcanbeusedatnightorinverylowvisibility,havinganexcellenttargetrecognitioncapabilityandprecision-detectioncapability.KeywordsInfraredimagedetection,Infraredimageprocessing,CMOS,DSP-SOC,ARM9.I.INTRODUCTIONInfrareddetectiontechnologyisahigh-techusingofinfrareddetectorstocaptureinfraredradiationtosearchandtrackthetarget.Itisfeaturedbyhighprecision,freefromtheeffectsofradiofrequencyinterferenceandcanbeoperateddayandnight.Thetechnologyisusuallyusedinfirealarmandpublicsafety.Anditcanberoughlydividedintonon-imagingandimagingdetectiontechnology.Non-imaginginfrareddetectiontechnologymakesuseofoneorseveralinfrareddetectorstocaptureandtrackthetarget,forwhichgivingoutinfraredradiationduetothermalmovementoftheatomsandmolecules.Becauseofthestructure,itcanbeeasilyinterferedbythenormalworkofclouds,foganddustimpact.Infraredimagingdetectionisusuallymakinguseofinfrareddetectorarraytodetecttheinfraredradiationgivenoutbythetarget.ThedetectorarrayisusuallyaCCDorCMOSimagesensorandtheimagequalityissimilartotelevision.Butitcanworkatnightandinverylowvisibility,whichthetelevisiondetectionsystemcanbedifficulttoworkin.Infraredimagingdetectiontechnologyhasnowbecomeamajordirectionofthefutureuse.Therearemanywaystoachieveinfraredimaging,mainlyusingthefollowingtwoways:(1)Multiplescanninginfraredimagingdetectorlineararrays;(2)Multiplenon-scanninginfraredimagingdetectorplanararrays.Theinfraredimagingdetectorhasbeendevelopedquicklysincethe1970s,fromlineararraytotheplanararray,andfromnear-infraredtofarinfrared.Thenumberofelementsofinfrareddetectorplanearrayisincreasing.Infraredimagingdetectionsystemhasagoodsensitivityandhighspatialresolution,awiderangeofdynamictrackingaswellastheeffectiverange,comparedtothenon-imaginginfrareddetection.Infraredimagingdetectionsystemhasbetterabilitytocompletetargetidentificationandprecisiondetection.Foraninfraredimagingdetectionsystem,theapplicationofimageprocessingandtargetrecognitionisakeyfeaturedifferencefromnon-imaginginfrareddetectionsystem.Thesensitivityofthedetectorarray,theperformanceofimageprocessingandtargetrecognitionalgorithm,theperformanceofdetectionalgorithmandthemechanicalmobilityalldeterminetheperformanceofthedetectionsystem.ThispaperwilldeepintothesearchofanearinfraredimagingdetectionsystembasedonDavinciDSPplatform,whichissuitableforvideoandimageprocessingduetoitsstructure.TheplatformhasanARM9coretransplantedwithLinuxoperatingsystemandaC64x+DSPcoretocompleteimagingalgorithmsinrealtime.Thepaperwillbestructuredasfollows;InSectionwewillexposetheframeworkofthesystem;InSectionwewilldeepintothestudyofhardwaredesignoftheimageprocessingandrecognition;InSectionwewilldescribeourapproachofsoftwarestructure,especiallytheLinuxoperatingsystemmigration;Insectionwewilldeepintothestudyoftheimageprocessingand4-154_978-1-4244-3864-8/09/$25.002009IEEETheNinthInternationalConferenceonElectronicMeasurement&InstrumentsICEMI2009recognitionalgorithmsandmethodssuitablefortheinfraredimagingdetectionsystem.II.SYSTEMFRAMEWORKThesystemcanberoughlydividedintothreeparts,thehardwarepart,thesoftwarepartandmechanicalpart.Allpartsaboveareanorganicwholeforthecloserelationmutually.Andtheblockdiagramofthesystemisshowedinfigure1below.Fig.1.BlockdiagramofthenearinfraredimagedetectionsystembaseonDavinciplatformAsshowninfigure1,theinfraredradiationfromthetrackedtargetisfocusedontheCMOSnearinfraredimagesensorthroughaninfraredopticallens.WithaCPLDthecorrespondingimagedataflowisscaledandbuffered.TheDavinciDSP-SOCwillacceptthedataflowafterward,andthencalculatethelocationofthetargetwiththecorrespondingimageprocessingalgorithms.Sincehasgotthelocationinformationofthetarget,theDSPthencontrolstheservosofhorizontalandvertical,lockingandtrackingtheinfraredtargetinrealtime.TheARM9coreintheDSP-SOCisoperatedwithLinux,whichisfreeandopensource.TheusercanhumanlyprogramthecoreDSPalgorithmsandtrackingalgorithmswithaPC.Withatouch-screenandTFTLCD,thesystemismuchmoreconvenientanduser-friendly.Duetothehighsensitivityandresolution,thenearinfraredimagingdetectionsystemcanbeusedatnightandinverylowvisibility,havinganexcellenttargetrecognitioncapabilityandprecision-detectioncapability.III.THEHARDWAREDESIGNTocapturetheinfraredimagesignalinverylowvisiblecircumstance,imagesensorwithhighsensitivityatnearinfraredbandshallbeapplied.ThemostpopularlyusedsensorsareCCDandCMOSimagesensor.Consideringthefeaturedifferencesofthebothintable1,CMOSimagesensorischoseninthedesignforitshighsensitivityaroundnearinfraredband,lowcostandlowpowerconsumption.Table1.FeaturedifferencesbetweenCCDandCMOSimagesensor.ParameterSensitivityatinfraredbandCostNoisePowerConsumptionCCDModerateHighLowHighCMOSHighLowHighLowThekeypartofthehardwareistheDSP-SOC,includinganARMcoreandaDSPcoreonthechip.TheARMcoreisusedasthemastertohandlecomplexsystemworkandDSPcoreastheslaver,handlingvideoprocessingandrecognitiontask.Togiveamuchmoreclearviewofthehardwarestructure,theblockdiagraminfigure2willbrieflyandclearlypresentsthevideoprocessingsubsystem(VPSS)onthechip.Fig.2.BlockdiagramofthevideoprocessingsubsystemThevideoprocessingsubsystemprovidesaninputinterface(videoprocessingfrontend,VPFE)forexternalimagingperipheralssuchasimagesensors,videodecoders,etc.;anoutputinterface(videoprocessingbackend,VPBE)fordisplaydevices,suchasanalogSDTVdisplays,digitalLCDpanels,HDTVvideoencoders,etc.Inadditiontotheseperipherals,thereisasetofcommonbuffermemoryandDMAcontroltoensureefficientuseoftheDDR2burstbandwidth.Thesharedbufferlogic/memoryisauniqueblockthatistailoredforseamlesslyintegratingtheVPSSintoanimage/videoprocessingsystem.ItisimperativethattheVPSSutilizeDDR2bandwidthefficientlyduetobothitslargebandwidthrequirementsandthereal-timerequirementsoftheVPSSmodules.BecauseitispossibletoconfiguretheVPSSmodulesinsuchawaythatDDR2bandwidthisexceeded,asetofuser-accessibleregistersisprovidedtomonitoroverflowsorfailuresindatatransfers.ThereforetheDSPissuitablefortheimagedetectiontask.AstheDDR2offershigh-bandwidthforthesystemoperation,thequalityofthePCBdesignofDDR2willaffectsthestabilityandrobustnessofthewholesystem.AsthehighestfrequencyonboardisnearlyGigahertz,themostchallengingworkinthedesignishowtoresolveElectroMagneticCompatibilityofthewholesystem.4-155TheNinthInternationalConferenceonElectronicMeasurement&InstrumentsICEMI2009Asrequired,thePCBshouldbeatleastappliedwithsixlayerstoresolveEMC,andtheminimumPCBstackuprequiredisshowninTable2.Eachsignallayerhasagroundplanetorefertoformmicrostripsandstriplines.Themultilayerdesignalsobenefitstothesignalintegrityandpowerintegrity.Table2.MinimumPCBstackuprequired.TheroutingofDDR2willbediscussedindetailinthefollowingparagraphs.TheCKandADDR_CTRLnetclassiscompletelysourcedbytheDSPtotheDDR2devices.EachnetisabalancedTroute,seeFigure3.ThelengthofsegmentAshouldbemaximizedandtheoveralllengthfromAtoBorAtoCshouldbeminimized.Ideally,thePCBdelayoftheCKnetclassisidenticaltothedelayfortheADDR_CTRLnetclass.AllnetsintheCKandADDR_CTRLnetclassesarematchedinlengthtoeachotherwithin100mils.AndthenetsintheCKnetclassarelaidoutasadifferentialpairtoachievehighreliabilityandnoiseimmunity.OthertracesshouldbekeptawayfromtheCKnetclasstracesbyatleast4wcenter-to-centerspacing(recallthatw=minimumtracewidth/space).TraceswithintheADDR_CTRLnetclassshouldbespacedatleast3wcenter-to-centerfromeachother.Tracesofothernetclassesshouldbekept4wawayfromtheADDR_CTRLnetclass.Fig.3.TopologyRequirementsforADDR_CTRLandClockNetClassesTheeightnetclassesthatmakeupthefourDQSBsandfourDQBbyteshavethesameroutingrules.NotethattheskewmatchingisrequiredbetweentheDQBnnetclassanditsassociatedDQSBnnetclass.ThesenetclassesaresourcedbytheDSPdeviceduringwritesandaresourcedbytheDDR2devicesduringreads.Ideally,thePCBdelayoftheDQSBnnetclassisidenticaltothedelayfortheDQBnnetclass.AllnetsintheDQSBnandDQBnnetclassshouldbematchedinlengthtoeachotherwithin100mils.ThelongesttracepermissibleisequaltothelongestManhattandistanceoftheDQSBnandDQBnnetclasses.OthertracesshouldbekeptawayfromtheDQSBnnetclasstracesbyatleast4wcenter-to-centerspacing.TraceswithintheDQBnnetclassesshouldbespacedatleast3wcenter-to-centerfromeachother.Tracesofothernetclassesshouldbekept4wawayfromtheDQBnnetclass.Togiveaclearviewofthehardwarerouting,thePCBoftheDSPtoDDR2isshownindetailinfigure4below.Fig.4.PCBoftheDSPinterfaceswithDDR2BeforethePCBwasmachining,simulationwassuccessfullycarriedoutwith133MHzclockrateand533MHzdataratetoensurethatthesystemwouldworkproperly,andthesimulationwaveofaddressbusanddatabusisshowninfigure5and6respectively.Fig.5.SimulationofDDR2addressesbusandclockbusat133MHz.Fig.6.SimulationofDDR2databusat533MHz4-156TheNinthInternationalConferenceonElectronicMeasurement&InstrumentsICEMI2009IV.THESOFTWAREDESIGNLinuxisaUnix-likeoperatingsystem.Afterdecadesofdevelopment,theLinuxoperatingsystembecomesmoreandmorematureandpopular.Featuredasopensource,theLinuxOSisfreeandflexibletouse.Furthermore,Linuxissuitableforworkstation,server,personalcomputerandembeddedsystem,foritsupportsmultiplearchitectures,CISCandRISC,suchasX86,ARM,MIPS,andsoon.Anembeddedapplicationsisusuallytransplantedwithanoperatingsystem,andLinuxisamostpopularonearoundtheworld,foritisopensourceandwithhighreliability.WewillmakefullexploitoftheLinuxOSanditstransplantationinourdesign.Firstofall,thekernelistheheartoftheLinuxoperatingsystem,whichoffersmanagementofprocess,managementofmemory,filesystem,devicecontrolandnetwork.Thefunctionblockisshowninfigure7.Fig.7.FunctionblockofthekernelofLinuxTheprocessmanagementmoduleisakeyblockoftheLinuxkernel,takingchargeofcreatingandterminatingprocess.Communicationthroughsignal,pipelineorcommunicationprimitivesamongdifferentprocessisabasicfunctionforthewholesystem,whichisaccomplishedbythekernel.Thememorymanagementmoduleistoensurealltheprocessescansafelysharethesystemmemory.Andwhatsmore,itshouldalsosupportvirtualmemorymodetohighlyimprovetheefficiencyofmemoryusage.Offeringacommoninterfaceforperipherals,thefilesystemmoduleisusedtosupportstorageanddriversforperipheralsandthevirtualfilesystemhidesdetailsofdifferenthardware.BootLoaderisthecoderunimmediatelyafterpoweron.WiththeBootLoader,hardwaredevicescanbeinitialized,andmassagescanbecreatedanddeliveredtothekernelthroughthecorrespondingmechanisms.AndthentheBootLoaderbringsthesystemtoapropermodeandloadthekernel.Figure8showsthebasicflowchartoftheBootLoader.TheBootLoaderiscloselydependedonthehardwareenvironment.Andbesidesofarchitecture,theBootLoaderalsodependsontheboardconfigurations,especiallyfortheembeddedapplications.Fig.8.FlowchartoftheBootLoaderAftertheBootLoaderinitializethewholesystemandthenreleasetheauthoritytotheLinuxkernel,thekernelthenworks.Thedevicedriveristheroutineworkingbetweenthehardwareandapplicationsinthekernelspace.Naturedasaconverterbetweenlogicdevicesandphysicaldevices,itstaskistoinitializeandmanipulatethecorrespondingI/Odevices.Thedevicedrivermasksdetailsofthehardwarefortheapplications.Withthedevicedriver,theapplicationscancontrolhardwaredeviceaseasyasmanipulatecommonfiles.Theapplicationsoftwareoftheinfraredimagedetectionsystemisdesignedtoaccomplishtheimageprocessingandrecognitiontaskswiththecorrespondingalgorithms.Thealgorithmswillbedetailedinthefollowingsection.V.IMAGINGPROCESSINGANDRECOGNITIONALGORITHMSANDMETHODSTheimageprocessingandrecognitionprogramiscompletedontheapplicationlayerofLinux.Andtheflowchartoftheapplicationisshowninfigure9.Besidesotherlayersdesign,wewillfocusontheimageprocessingandrecognitionalgorithmsandmethodsusedintheapplicationlayeraccordingtotheflowchart.Theinfraredimageisusuallymonochromeorpseudo-colouredandwithlowcontrast,sometimesmightbeunclearordifficulttorecognize.Forexample,itmightbenoteasytofigureoutthebirdhiddeninlushfoliageinapicturetakenatnightorinverylowvisibility.Imageenhancementisintroducedtoenlargethedetailsingrayscaleorspatialtoobtainaclearimage.Therearesomemethodsusedinourdesign,suchasgrayscaleenhancement,contrastenhancementandhistogramadjustment.Contrastenhancementmagnifiesntimesthegrayvalueoftheentirepixels,thatis;g11g12g11g12g,xynfxyg32g1174-157TheNinthInternationalConferenceonElectronicMeasurement&InstrumentsICEMI2009Thegrayvalueintheoriginalimageisg11g12,fxyandthegrayvalueinthecontrastenhancedimageisg11g12,gxy,whichisntimesthegrayvalueintheoriginalimage.Histogramadjustmentisamethodtocompressthegrayvaluewithfewerpixels,andextendthegrayvaluewithmorepixels.Aftercontrastenhancementandhistogramadjustment,detailsintheimagecanbeexposed.Andthecorrespondinghistogramisflatteredaftertheprocess.Theoriginalimageoftendistributedwithrandomnoise,makingtheimagedeteriorated.Inordertogetridofsuchnoise,imagesmoothingormedianfilterareused.Withtherandomnoiseoftheoriginalimagebeingremoved,sharpdetailsarealsolostduringtheprocess.Fig.9.FlowchartoftheapplicationAftertheimageprocessing,imagerecognitionisfinallyusedtofulfilltheinfraredimagingdetectiontask.Edgedetectionandextractionbasedondifferentialisapplied.Duetothedramaticchangesingrayvalueofthebrink,itisclearthatdifferentialfunctioncanwellextractthechanges.Supposeg11g12,xypresentsthelocationofapixel,andg11g12,fxypresentsthegrayvalueofit.Withavectorg11g12g11g12,xyGxyffg32,theedgecanbeeasilyfiguredoutbythegradient.xfandyfarethedifferentialalonghorizontalandvertical,calculatedwiththefollowingequations.g11g12g11g12g11g12g11g12g961,1,xyffxyfxyffxyfxyg32g14g16g32g14g16Sotheintensityoftheedgeis22xyffg14,andthedirectionisalongthevectorg11g12,xyff.Anthermethodusuallyusedisedgedetectionandextractionbasedontemplatematching.Andtemplatematchingisresponsibleforresearchingtheconsistencyofimageandthecorrespondingtemplate.Patternrecognitionisappliedtoclassifypatternsfromeachothertodeterminewhethertheobjectisthetargetornot.Andthefollowingmethodsarethechoices;Templatematching;statisticalclassification;andartificialneuralnetwork.Templatematchingistheearliestandeasiestwayforimagerecognition,whichissomewhatoneofstatisticalrecognition.Matchingisageneraloperationdenotedbycorrelationcoefficient,usedtodefinethesimilaritybetweenthetemplatesandthesamples.Whenusingtemplatematching,templ