Компютърно зрение

Определение

Computervisionisasimulationofbiologicalvisionusingcomputersandrelatedequipment.Itsmaintaskistoobtainthree-dimensionalinformationofthecorrespondingscenebyprocessingthecollectedpicturesorvideos,justlikehumansandmanyotherkindsofcreaturesdoeveryday.

Computervisionisasubjectofhowtousecamerasandcomputerstoobtainthedataandinformationweneedaboutthesubject.Връхutitvividly,itistoinstalleyes(cameras)andbrains(algorithms)onthecomputersothatthecomputercanperceivetheenvironment.TheChineseidiom"seeingisbelieving"andthewesternsaying"Onepictureisworthtenthousandwords"expresstheimportanceofvisiontomankind.Itisnotdifficulttoimaginehowbroadtheapplicationprospectsofmachineswithvisioncanbe.

Computervisionisnotonlyanengineeringfield,butalsoachallengingandimportantresearchfieldinthescientificfield.Computervisionisacomprehensivediscipline,ithasattractedresearchersfromvariousdisciplinestoparticipateinitsresearch.Theseincludecomputerscienceandengineering,signalprocessing,physics,appliedmathematicsandstatistics,neurophysiologyandcognitivescience.

Анализ

Visionisanintegralpartofvariousintelligent/autonomoussystemsinvariousapplicationfields,suchasmanufacturing,inspection,documentanalysis,medicaldiagnosis,andmilitary.Becauseofitsimportance,someadvancedcountries,suchastheUnitedStates,listcomputervisionresearchasamajorbasicprobleminscienceandengineeringthathasawide-rangingimpactoneconomyandscience,theso-calledgrandchallenge.Thechallengeofcomputervisionistodevelopvisioncapabilitiescomparabletohumansforcomputersandrobots.Machinevisionrequiresimagesignals,textureandcolormodeling,geometricprocessingandreasoning,andobjectmodeling.Acapablevisionsystemshouldtightlyintegratealltheseprocesses.Asadiscipline,computervisionbeganintheearly1960s,butmanyimportantadvancesinthebasicresearchofcomputervisionweremadeinthe1980s.Computervisioniscloselyrelatedtohumanvision.Acorrectunderstandingofhumanvisionwillbeverybeneficialtotheresearchofcomputervision.Forthiswewillfirstintroducehumanvision.

Принцип

Computervisionistheuseofvariousimagingsystemsinsteadofvisualorgansasinput-sensitivemeans,andcomputersinsteadofthebraintocompleteprocessingandinterpretation.Theultimateresearchgoalofcomputervisionistoenablecomputerstoobserveandunderstandtheworldthroughvisionlikehumans,andhavetheabilitytoadapttotheenvironmentautonomously.Agoalthatcanonlybeachievedafterlong-termefforts.Therefore,beforeachievingthefinalgoal,themid-termgoalofpeople'seffortsistoestablishavisionsystemthatcancompletecertaintasksbasedonacertaindegreeofintelligencewithvisualsensitivityandfeedback.Forexample,animportantapplicationareaof​​computervisionisthevisualnavigationofautonomousvehicles.Thereisnoconditiontorealizeasystemthatcanrecognizeandunderstandanyenvironmentandcompleteautonomousnavigationlikehumans.Therefore,theresearchgoalofpeople'seffortsistoachieveavisualassisteddrivingsystemthathasroadtrackingcapabilitiesonexpresswaysandcanavoidcollisionswithvehiclesinfront.Thepointtobepointedouthereisthatinthecomputervisionsystem,thecomputerreplacesthehumanbrain,butitdoesnotmeanthatthecomputermustcompletetheprocessingofvisualinformationaccordingtothemethodofhumanvision.Computervisioncanandshouldprocessvisualinformationaccordingtothecharacteristicsofthecomputersystem.However,thehumanvisualsystemisbyfarthemostpowerfulandcompletevisualsystemknowntopeople.Asyouwillseeinthefollowingchapters,thestudyofhumanvisualprocessingmechanismswillprovideinspirationandguidanceforcomputervisionresearch.Therefore,thecomputerinformationprocessingmethodisusedtostudythemechanismofhumanvisionandestablishthecalculationtheoryofhumanvision.ResearchinthisareaiscalledComputationalVision.Computationalvisioncanbeconsideredasaresearchfieldincomputervision.

Свързани

Therearemanydisciplineswhoseresearchgoalsaresimilartoorrelatedtocomputervision.Thesesubjectsincludeimageprocessing,patternrecognitionorimagerecognition,sceneanalysis,imageunderstanding,etc.Computervisionincludesimageprocessingandpatternrecognition.Inaddition,italsoincludesthedescriptionofspatialshapes,geometricmodeling,andtheprocessofrecognition.Realizingimageunderstandingistheultimategoalofcomputervision.

Обработка на изображение

Обработка на изображениеtechnologyconvertstheinputimageintoanotherimagewithdesiredcharacteristics.Forexample,theoutputimagecanbeprocessedtohaveahighersignal-to-noiseratio,orenhancedprocessingcanbeusedtohighlightthedetailsoftheimagetofacilitateinspectionbytheoperator.Incomputervisionresearch,imageprocessingtechnologyisoftenusedforpreprocessingandfeatureextraction.

Разпознаване на шаблон

Разпознаване на шаблонtechnologydividesimagesintopredeterminedcategoriesbasedonthestatisticalcharacteristicsorstructuralinformationextractedfromtheimage.Forexample,textrecognitionorfingerprintrecognition.Incomputervision,patternrecognitiontechnologyisoftenusedtoidentifyandclassifycertainpartsofanimage,suchassegmentedregions.

Образно разбиране

Givenanimage,theimageunderstandingprogramnotonlydescribestheimageitself,butalsodescribesandinterpretsthescenerepresentedbytheimage,inordertomakeananalysisofthecontentrepresentedbytheimage.Decide.Intheearlydaysofartificialintelligencevisionresearch,thetermsceneanalysiswasoftenusedtoemphasizethedifferencebetweentwo-dimensionalimagesandthree-dimensionalscenes.Inadditiontocompleximageprocessing,imageunderstandingalsorequiresknowledgeaboutthephysicallawsofsceneimagingandknowledgerelatedtothecontentofthescene.

Whenestablishingacomputervisionsystem,itisnecessarytousetherelevanttechnologiesintheabovedisciplines,butthecontentofcomputervisionresearchismoreextensivethanthesedisciplines.Theresearchofcomputervisioniscloselyrelatedtotheresearchofhumanvision.Inordertoachievethegoalofestablishingageneral-purposecomputervisionsystemsimilartothehumanvisionsystem,itisnecessarytoestablishacomputertheoryofhumanvision.

Текущо състояние

Theoutstandingfeatureofthecomputervisionfieldisitsdiversityandimperfection.Pioneersinthisfieldcanbetracedbacktoearliertimes,butitwasnotuntilthelate1970swhentheperformanceofcomputerswasimprovedtohandlelarge-scaledatasuchasimagesthatcomputervisionreceivedformalattentionanddevelopment.However,thesedevelopmentsoftenoriginatefromtheneedsofotherdifferentfields,sowhatismeantby"computervisionproblems"hasneverbeenformallydefined.Naturally,thereisnoformulaforhow"computervisionproblems"shouldbesolved.

Nevertheless,peoplehavebeguntomastersomeofthemethodstosolvespecificcomputervisiontasks.Unfortunately,thesemethodsareusuallyonlyapplicabletoagroupofnarrowtargets(suchas:faces,fingerprints,text,etc.),sotheycannotbeWidelyusedindifferentoccasions.

Theapplicationofthesemethodsisusuallyacomponentofsomelarge-scalesystemsthatsolvecomplexproblems(suchasmedicalimageprocessing,qualitycontrolandmeasurementinindustrialmanufacturing).Inmostpracticalapplicationsofcomputervision,computersarepresettosolvespecifictasks.However,methodsbasedonmachinelearningarebecomingmoreandmorepopular.Oncetheresearchofmachinelearningisfurtherdeveloped,thefuture"generalpurpose"computervisionapplicationsmaybeabletocometrue.

Oneofthemainissuesstudiedbyartificialintelligenceis:howtomakethesystemhave"planning"and"decision-makingcapabilities"?Soastomakeitcompleteaspecifictechnicalaction(forexample:movearobotthroughaspecificenvironment).Thisproblemiscloselyrelatedtothecomputervisionproblem.Here,thecomputervisionsystemactsasaperceptron,providinginformationfordecision-making.Otherresearchdirectionsincludepatternrecognitionandmachinelearning(whichalsobelongtothefieldofartificialintelligence,buthaveanimportantconnectionwithcomputervision).Asaresult,computervisionisoftenregardedasabranchofartificialintelligenceandcomputerscience.

Physicsisanotherfieldthathasanimportantconnectionwithcomputervision.

Thegoalofcomputervisionistofullyunderstandtheelectromagneticwaves-mainlyvisiblelightandinfraredlight-theimageformedbythereflectionofthesurfaceoftheobject,andthisprocessisbasedonopticalphysicsandsolid-statephysics.Somecutting-edgeimageperceptionsystemswillevenbeappliedtoquantummechanicstheorytoanalyzetherealworldrepresentedbyimages.Atthesametime,manymeasurementproblemsinphysicscanalsobesolvedbycomputervision,suchasfluidmotion.Becauseofthis,computervisioncanalsobeseenasanextensionofphysics.

Anotherimportantfieldisneurobiology,especiallythepartofthebiologicalvisualsystem.

Throughoutthe20thcentury,humanshaveconductedextensivestudiesontheeyes,neurons,andbraintissuesofvariousanimalsrelatedtovisualstimulation.Thesestudieshaveledtosome"natural"Thedescriptionofhowthevisualsystemworks(althoughitisstillabitrough)hasalsoformedasub-fieldofcomputervision-peopletrytobuildartificialsystemsthatcansimulatethevisualoperationsoflivingbeingswithvaryingdegreesofcomplexity.Atthesametime,inthefieldofcomputervision,somemethodsbasedonmachinelearningalsorefertosomebiologicalmechanisms.

Anotherrelatedfieldofcomputervisionissignalprocessing.Manyprocessingmethodsrelatedtounitvariablesignals,especiallytheprocessingoftime-varyingsignals,cannaturallybeextendedtotheprocessingmethodsofbinaryvariablesignalsormultivariatesignalsincomputervision.However,duetotheuniquepropertiesofimagedata,manymethodsdevelopedincomputervisioncannotfindacorrespondingversionintheunitsignalprocessingmethod.Oneofthemaincharacteristicsofthesemethodsistheirnon-linearityandthemulti-dimensionalityofimageinformation.Theabovetwopoints,aspartofcomputervision,formaspecialresearchdirectioninsignalprocessing.

Inadditiontothefieldsmentionedabove,manyresearchtopicscanalsobetreatedaspurelymathematicalproblems.Forexample,manyproblemsincomputervisionarebasedonstatistics,optimizationtheory,andgeometry.

Howtoimplementexistingmethodsthroughvarioussoftwareandhardware,orhowtomodifythesemethods,soastoobtainreasonableexecutionspeedwithoutlosingsufficientaccuracy,isthemainissueinthefieldofcomputervisiontoday.Subject.

Приложение

Mankindisenteringtheinformationage,andcomputerswillincreasinglyenteralmostallfields.Ontheonehand,morepeoplewithoutprofessionalcomputertrainingalsoneedtousecomputers.Ontheotherhand,thefunctionsofcomputersaregettingstrongerandstronger,andthemethodsofusingthemaregettingmoreandmorecomplicated.Thiscreatesasharpcontradictionbetweentheflexibilityofpeopleinconversationandcommunicationandthestrictnessandrigidityrequiredwhenusingcomputers.Humanscanexchangeinformationwiththeoutsideworldthroughvision,hearing,andlanguage,andcanexpressthesamemeaningindifferentways.However,computersarerequiredtowriteprogramsstrictlyinaccordancewithvariousprogramminglanguages,sothatcomputerscanrun.Inordertoenablemorepeopletousecomplexcomputers,itisnecessarytochangethepastsituationwherepeopleadapttocomputersandmemorizecomputerusagerulesbyrote.Instead,letthecomputeradapttopeople'shabitsandrequirements,andexchangeinformationwithpeopleinthewaypeopleareusedto,thatis,letthecomputerhavetheabilitytosee,hear,andspeak.Atthistime,thecomputermusthavetheabilityoflogicalreasoninganddecision-making.Acomputerwiththeabovecapabilitiesisanintelligentcomputer.

Intelligentcomputersnotonlymakecomputersmoreconvenientforpeopletouse,butatthesametime,ifsuchcomputersareusedtocontrolvariousautomationdevices,especiallyintelligentrobots,theseautomationsystemsandintelligentrobotscanadapttotheenvironment,andTheabilitytomakedecisionsindependently.Thiscanreplacepeople'sheavyworkonvariousoccasions,orreplacepeopletocompletetasksinvariousdangerousandharshenvironments.

Приложениеsrangefromtasks,suchasindustrialmachinevisionsystems,forexample,inspectionofbottlesontheproductionlinetoacceleratethrough,researchintoartificialintelligenceandcomputersorrobots,whichcanunderstandtheworldaroundthem.Thereisasignificantoverlapinthefieldsofcomputervisionandmachinevision.Computervisioninvolvesthecoretechnologyusedinautomatedimageanalysisinmanyfields.Machinevisionusuallyreferstoaprocessthatcombinesautomaticimageanalysiswithothermethodsandtechnologiestoprovideautomaticdetectionandrobotguidanceinindustrialapplications.Inmanycomputervisionapplications,computersarepre-programmedtosolvespecifictasks,butlearning-basedmethodsarenowbecomingmoreandmorecommon.Examplesofcomputervisionapplicationsincludethoseusedinsystems:

(1) Контролиране на процеса, като промишлен робот;

(2) Навигация, като например от автономни автомобили или мобилни роботи;

(3) Открити събития, като видеонаблюдение и преброяване на хора;

(4) Организиране на информация, например, индексни бази данни за изображения и последователности от изображения;

(5)Modelingobjectsorenvironments,suchasmedicalimageanalysissystemsorterrainmodels;

(6) Взаимодействие, например, при въвеждане в устройство за взаимодействие компютър-човек;

(7) Автоматично откриване, например, в производствени приложения.

Themostprominentapplicationareasaremedicalcomputervisionandmedicalimageprocessing.Thefeatureinformationofthisareaisextractedfromtheimagedataforthepurposeofmedicaldiagnosisofthepatient.Usually,theimagedataisintheformofmicroscopeimages,X-rayimages,angiographyimages,ultrasoundimagesandtomographicimages.Anexampleoftheinformationthatcanbeextractedfromsuchimagedataisthedetectionoftumors,atherosclerosisorothermalignantchanges.Itcanalsobethesizeoftheorgan,bloodflow,etc.Thisfieldofapplicationalsosupportsthemeasurementofmedicalresearchbyprovidingnewinformation,forexample,onthestructureofthebrain,oraboutthequalityofmedicaltreatment.Theapplicationofcomputervisioninthemedicalfieldalsoincludesenhancingimagesthatareinterpretedbyhumans,suchasultrasoundimagesorX-rayimages,toreducetheeffectsofnoise.

Thesecondapplicationareaof​​computervisionisinindustry,sometimescalledmachinevision,whereinformationisextractedtosupportthepurposeofthemanufacturingprocess.Anexampleisqualitycontrol,wheretheinformationorfinalproductisautomaticallydetectedinordertofinddefects.Anotherexampleisthatthepositionanddetailorientationbeingpickeduparemeasuredbytheroboticarm.Machinevisionisalsousedextensivelyintheprocessofagriculture,frombulkmaterials,thisprocessiscalledtheremovalofunwantedthings,opticalsortingoffood.

Militaryapplicationsareprobablyoneofthelargestareasofcomputervision.Themostobviousexampleisthedetectionofenemysoldiersorvehiclesandmissileguidance.Moreadvancedsystemsguidethemissiletotheareawherethemissileissent,ratherthanaspecifictarget,andmakeaselectionwhenthemissilereachesthetargetintheareabasedonlocallyacquiredimagedata.Modernmilitaryconcepts,suchas"battlefieldperception",meanthatvarioussensors,includingimagesensors,provideawealthofrelevantcombatscenariosthatcanbeusedtosupportstrategicdecision-makinginformation.Inthiscase,automaticdataprocessingisusedtoreducecomplexityandfuseinformationfrommultiplesensorstoimprovereliability.

Anewerapplicationareaisautonomousvehicles,whichincludediving,landvehicles(smallrobotswithwheels,carsortrucks),aerialworkvehiclesandunmannedaerialvehicles(UAV).Thelevelofautonomyrangesfromcompletelyindependent(unmanned)vehiclestocars,wherecomputervision-basedsystemssupportdriverprogramsorexperimentsindifferentsituations.Afullyautonomouscarusuallyusescomputervisiontonavigatewhenitknowswhereitis,ortheenvironmentusedforproduction(mapSLAM)andfordetectingobstacles.Itcanalsobeusedtodetectspecificeventsforspecifictasks,forexample,aUAVlookingforforestfires.Examplesofsupportsystemsarecarsinobstaclewarningsystems,andautonomouslandingsystemsforaircraft.Severalautomakershavedemonstratedthesystem'sautonomousdrivingofcars,butthetechnologyhasnotreachedacertainlevelbeforeitcanbeputonthemarket.Thereareplentyofexamplesofmilitaryautonomousmodels,fromadvancedmissiles,unmannedaerialvehiclesforreconnaissancemissionsormissileguidance.Spaceexplorationisalreadyusingcomputervision,autonomousvehiclessuchasNASA’sMarsExplorationRoverandtheEuropeanSpaceAgency’sExoMarsMarsRover.

Други области на приложение включват:

(1) Филми и предавания, които поддържат производството на визуални ефекти, например проследяване на камерата (съпоставяне на движение).

(2) Мониторинг.

Прилики и разлики

Computervision,imageprocessing,imageanalysis,robotvisionandmachinevisionarecloselyrelateddisciplines.Ifyouopenthetextbookswiththeabovenames,youwillfindthattheyhaveaconsiderableoverlapintechnologyandapplicationareas.Thisshowsthatthebasictheoriesofthesedisciplinesareroughlythesame,anditevenmakespeoplesuspectthattheyarethesamedisciplineswithdifferentnames.

Computer vision

However,variousresearchinstitutions,academicjournals,conferences,andcompaniesoftenclassifythemselvesasaparticularfield,soavarietyofcharacteristicsthatdistinguishthesedisciplineshavebeenbroughtup.Amethodofdistinctionwillbegivenbelow,althoughitcannotbesaidthatthismethodofdistinctioniscompletelyaccurate.

Theresearchobjectofcomputervisionismainlyathree-dimensionalscenemappedtoasingleormultipleimages,suchasthereconstructionofathree-dimensionalscene.Theresearchofcomputervisionislargelyfocusedonthecontentoftheimage.

Theresearchobjectsofimageprocessingandimageanalysisaremainlytwo-dimensionalimages,whichrealizeimagetransformation,especiallyforpixel-leveloperations,suchasimagecontrastimprovement,edgeextraction,denoisingandgeometrictransformationssuchasimagerotation.Thisfeatureshowsthattheresearchcontentofimageprocessingorimageanalysishasnothingtodowiththespecificcontentoftheimage.

Machinevisionmainlyreferstothevisualresearchintheindustrialfield,suchasthevisionofautonomousrobots,andthevisionforinspectionandmeasurement.Thisshowsthatinthisfield,throughsoftwareandhardware,imageperceptionandcontroltheoryisoftencloselycombinedwithimageprocessingtoachieveefficientrobotcontrolorvariousreal-timeoperations.

Разпознаване на шаблонusesvariousmethodstoextractinformationfromsignals,mainlyusingstatisticaltheories.Oneofthemaindirectionsinthisfieldistoextractinformationfromimagedata.

Thereisanotherfieldcalledimagingtechnology.Theinitialresearchcontentinthisfieldismainlytomakeimages,butsometimesalsoinvolvesimageanalysisandprocessing.Forexample,medicalimagingincludesalargenumberofimageanalysisinthemedicalfield.

Forallthesefields,apossibleprocessisthatyouworkinacomputervisionlaboratory,youareengagedinimageprocessingatwork,andfinallysolvetheproblemsinthefieldofmachinevision,andthenpublishyourresultsinAtthemeetingofpatternrecognition.

проблеми

Almosteveryspecificapplicationofcomputervisiontechnologymustsolveaseriesofthesameproblems.Theseclassicproblemsinclude:

Признание

Acomputervision,imageprocessingandmachinevisioncommonclassicproblemistodeterminewhetherasetofimagedatacontainsaspecificObject,imagefeatureormovementstate.Thisproblemcanusuallybesolvedautomaticallybyamachine,butsofar,thereisnosinglemethodthatcandetermineawiderangeofsituations:recognizeanyobjectinanyenvironment.Theexistingtechnologycanandcanonlywellsolvetherecognitionofspecifictargets,suchassimplegeometricpatternrecognition,facerecognition,printedorhandwrittendocumentrecognition,orvehiclerecognition.Andtheserecognitionsneedtohavespecifiedlighting,backgroundandtargetposturerequirementsinaspecificenvironment.

Generalrecognitionhasevolvedintoseveralslightlydifferentconceptsondifferentoccasions:

Признание(narrowsense):Foroneormorepre-definedorlearnedObjectsorobjectsarerecognized,andtheirtwo-dimensionalpositionorthree-dimensionalpostureisusuallyprovidedduringtherecognitionprocess.

Identification:Identifythesingleobjectitself.Forexample:therecognitionofacertainface,therecognitionofacertainfingerprint.

Monitoring:Discoverspecificsituationcontentfromimages.Forexample:thediscoveryofabnormalskillsincellsortissuesinmedicine,andthediscoveryofpassingvehiclesbytrafficmonitoringequipment.Monitoringisoftentodiscoverspecialareasintheimagethroughsimpleimageprocessing,whichprovidesastartingpointforsubsequentmorecomplexoperations.

Идентифицирани са няколко конкретни насоки за приложение:

Content-basedimageextraction:Findallpicturescontainingspecifiedcontentinahugeimagecollection.Thespecifiedcontentcantakemanyforms,suchasaredroughlycircularpattern,orabicycle.Thesearchforthelatterkindofcontenthereisobviouslymorecomplicatedthantheformer,becausetheformerdescribesalow-levelintuitivevisualfeature,whilethelatterinvolvesanabstractconcept(orhigh-levelvisualfeature).Thatis,"bicycle",theobviouspointisthattheappearanceofthebicycleisnotfixed.

Poseevaluation:Evaluationofthepositionordirectionofanobjectrelativetothecamera.Forexample:theassessmentofthepostureandpositionoftheroboticarm.

Opticalcharacterrecognitionrecognizesanddiscriminatesprintedorhandwrittentextinanimage,andtheusualoutputistoconvertitintoaneasy-to-editdocumentform.

Движение

Themonitoringofobjectmotionbasedonsequenceimagesincludesmanytypes,suchas:

Selfmotion:monitorthethree-dimensionalrigidmotionofthecamera.

Проследяване на изображения: Проследяване на движещи се обекти.

Реконструкция на сцена

Giventwoormoreimagesoravideoofascene,scenereconstructionseekstobuildacomputermodel/three-dimensionalmodelofthescene.Thesimplestcaseistogenerateasetofpointsinthree-dimensionalspace.Inmorecomplexsituations,acompletethree-dimensionalsurfacemodelwillbebuilt.

Възстановяване на изображението

Thegoalofimagerestorationistoremovenoiseintheimage,suchasinstrumentnoise,blur,etc.

Система

Thestructureofthecomputervisionsystemlargelydependsonitsspecificapplicationdirection.Someworkindependentlyandareusedtosolvespecificmeasurementorinspectionproblems;someappearasapartofalargecomplexsystem,suchasworkingwithmechanicalcontrolsystems,databasesystems,andman-machineinterfacedevices.Thespecificimplementationmethodofthecomputervisionsystemisalsodeterminedbyitsfunction-whetheritisfixedinadvanceorisautomaticallylearnedandadjustedduringoperation.However,therearesomefunctionsthatalmosteverycomputersystemneeds:

Придобиване на изображение

Adigitalimageisproducedbyoneormoreimagesensors,hereThesensorcanbeavarietyofphotosensitivecameras,includingremotesensingequipment,X-raytomography,radar,ultrasonicreceivers,andsoon.Dependingonthedifferentperceptrons,thegeneratedpicturecanbeanordinarytwo-dimensionalimage,athree-dimensionalimagegrouporanimagesequence.Thepixelvalueofthepictureoftencorrespondstotheintensityoflightinoneormorespectralbands(grayscaleorcolorimage),butitcanalsoberelatedtovariousphysicaldata,suchasthedepthandabsorbanceofsoundwaves,electromagneticwavesornuclearmagneticresonanceOrreflectivity.

Предварителна обработка

Beforeimplementingspecificcomputervisionmethodsontheimagetoextractcertainspecificinformation,oneorsomepreprocessingisoftenusedtomaketheimagemeettherequirementsofsubsequentmethodsRequire.Forexample:

Подизвадка за осигуряване на правилните координати на изображението;

Smoothdenoisingtofilteroutthedevicenoiseintroducedbythesensor;

ImprovethecontrasttoensuretherealizationRelevantinformationcanbedetected;

Adjustthescalespacetomaketheimagestructuresuitableforlocalapplications.

Извличане на функции

Extractfeaturesofvariouscomplexityfromtheimage.Forexample:

Линия,извличане на ръбове;

Localizedfeaturepointdetectionsuchascornerdetection,spotdetection;

MorecomplexfeaturesmayberelatedtotheimageThetextureshapeormovementisrelated.

Откриване на сегментация

Intheprocessofimageprocessing,itissometimesnecessarytosegmenttheimagetoextractvaluablepartsforsubsequentprocessing,suchas

screeningFeaturepoints;

Segmentthepartofoneormorepicturesthatcontainsaspecifictarget.

Разширена обработка

Atthispoint,thedataoftenhasasmallamount,suchasthepartoftheimagethatisconsideredtocontainthetargetobjectafterpreviousprocessing.Theprocessingatthistimeincludes:

Verifywhetherthedataobtainedmeetstheprerequisiterequirements;

Estimatespecificcoefficients,suchasthetarget’sattitudeandvolume;

вид.

Разширена обработкаhasthemeaningofunderstandingimagecontent.Itisahigh-levelprocessingincomputervision.Itismainlybasedonimagesegmentationtounderstandthesegmentedimageblocks,suchasrecognitionandotheroperations..

Изисквания

Theinfluenceoflightsourcelayoutneedstobecarefullyconsidered.

Изберете правилната група лещи, като вземете предвид увеличението, пространството, размера, изкривяването...

Изберете правилната камера (CCD), имайки предвид функцията, спецификациите, стабилността, издръжливостта...

Visualsoftwaredevelopmentneedstorelyontheaccumulationofexperience,trymoreandthinkaboutthewaytosolvetheproblem.

Theultimategoalistocontinuouslyimprovetheaccuracyofcreationandshortentheprocessingtime.

край.

Конференция

Връх

ICCV:InternationalКонференцияonComputerVision,InternationalComputerVisionКонференция

CVPR:InternationalКонференцияonComputerVisionandPatternПризнание,InternationalКонференцияonComputerVisionandPatternПризнание

ECCV:EuropeanКонференцияonComputerVision,EuropeanКонференцияonComputerVision

По-добре

ICIP:InternationalКонференцияonImageProcessing,InternationalКонференцияonImageProcessing

BMVC:BritishMachineVisionКонференция,BritishMachineVisionКонференция

ICPR:InternationalКонференцияonPatternПризнание,InternationalКонференцияonPatternПризнание

ACCV:AsianКонференцияonComputerVision,AsianКонференцияonComputerVision

Журнал

Връх

PAMI:IEEETransactionsonPatternАнализandMachineIntelligence,IEEEPatternАнализЖурналofMachineIntelligence

IJCV:InternationalЖурналonComputerVision,InternationalЖурналofComputerVision

По-добре

TIP:IEEETransactionsonImageProcessing,IEEEImageProcessingMagazine

CVIU:ComputerVisionandImageUnderstanding,ComputerVisionandImageUnderstanding

PR: Разпознаване на образи, Разпознаване на образи

PRL:PatternПризнаниеLetters,PatternПризнаниеExpress

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