图像处理-毕设论文外文翻译(翻译+原文)

Imageprocessingisnotaonestepprocess．WeareabletodistinguishbetweenseveralstepswhichmustbeperformedoneaftertheotheruntilwecanextractthedataofinterestfromtheobservedsceneprocessingschemeisbuiltupassketchedinFigofthedifferentphasesofimageprocessing.．Inthiswayahierarchical．ThefiguregivesanoverviewWiththeproblemsoftrafficaremoreandmoreserious.ThusIntelligentTransportSystem(ITS)comesout.Thesubjectoftheautomaticrecognitionoflicenseplateisoneofthemostsignificantsubjectsthatareimprovedfromtheconnectionofcomputervisionandpatternrecognition.TheimageimputedtothecomputerisdisposedandanalyzedinordertolocalizationthepositionandrecognitionthecharactersonthelicenseplateexpressthesecharactersintextstringformThelicenseplaterecognitionsystem(LPSR)hasimportantapplicationinITS.InLPSR,thefirststepisforlocatingthelicenseplateinthecapturedimagewhichisveryimportantforcharacterrecognition.Therecognitioncorrectionrateoflicenseplateisgovernedbyaccuratedegreeoflicenseplatelocation.Inthispaper,severalofmethodsinimagemanipulationarecomparedandanalyzed,thencomeouttheresolutionsforlocalizationofthecarplate.Theexperiencesshowthatthegoodresulthasbeengotwiththesemethods.Themethodsbasedonedgemapandfrequencyanalysisisusedintheprocessofthelocalizationofthelicenseplate,thatistosay,extractingthecharacteristicsofthelicenseplateinthecarimagesafterbeingcheckedupforuntiltheprobablyareaoflicenseimageprocessing,it’s．ItisthekeystepintheAwholechainofprocessingstepsisnecessarytoanalyzeandidentifyobjects．First，adequatefilteringproceduresmustbeappliedinordertodistinguishtheobjectsofinterestfromotherobjectsandthebackgroundEssentiallyfroman（orseveralimagesoneormorefeatureimagesareextracted．Thebasictoolsforthistaskareaveragingandedgedetectionandtheanalysisofsimpleneighborhoodsandcomplexpatternsknownastextureinimageprocessing．Animportantfeatureofanobjectisalsoitsmotion．Techniquestodetectanddeterminemotionarenecessary．Thentheobjecthastobeseparatedfromthebackground．Thismeansthatregionsofconstantfeaturesanddiscontinuitiesmustbeidentified．Thisprocessleadstoa，weobtainparameterstoestimatetheirripenessortodetectdamagebyparasitesTherearemanymedicalapplicationswheretheessentialproblemistodetectpathologi-alchanges．Aclassicexampleistheanalysisofaberrationsinchromosomes．Characterrecognitioninprintedandhandwrittentextisanotherexamplewhichhasbeenstudiedsinceimageprocessingbeganandstillposessignificantdifficulties．arereading．ThisisalsothefinalstepofimageprocessingwewatchthetraffictocrossastreetsafelyWealldothiswithoutknowinghowthevisualsystemworks．Forsometimesnow，imageprocessingandcomputer-graphicshavebeentreatedastwodifferentareasimage．Tohandleimageprocessingorcomputergraphicsworkfromthesameknowledge．Weneedtoknowtheinteractionbetweenilluminationandobjects，howathree-dimensionalsceneisprojectedontoanimageplane，etc．Therearestillquiteafewdifferencesbetweenanimageprocessingandagraphicsworkstation．Butwecanenvisagethat，whenthesimilaritiesandinterrelationsbetweencomputergraphicsandimageprocessingarebetterunderstoodandtheproperhardwareisdeveloped，wewillseesomekindofgeneral-purposeworkstationinthefuturewhichcanhandlecomputergraphicsaswellasimageprocessingtasks[5]．Theadventofmultimedia，i.e.，theintegrationoftext，images，sound，andmovies，willfurtheracceleratetheunificationofcomputergraphicsandimageprocessing.InJanuary1980ScientificAmericanpublishedaremarkableimagecalledPlume2，thesecondofeightvolcaniceruptionsdetectedontheJovianmoonbythespacecraftVoyager1on5March1979Thepicturewasalandmarkimageininterplanetaryexploration—thefirsttimeaneruptingvolcanohadbeenseeninspace．Itwasalsoatriumphforimageprocessing．Satelliteimageryandimagesfrominterplanetaryexplorershaveuntilfairlyrecentlybeenthemajorusersofimageprocessingtechniquesofbombingraids．Withtheadventofsatelliteimageryinthelate1960scomputer-basedworkbeganandthecolorcompositesatelliteimagessometimescomputersandimagecollectiondeviceslikedigitalcamerasandscannershaveseenamigrationofimageprocessingtechniquesintothepublicdomain．Classicalimageprocessingtechniquesareroutinelyemployedbygraphicdesignerstomanipulatephotographicandgeneratedimagery，eithertoArecentmainstreamapplicationofimageprocessingisthecompressionofimages—eitherfortransmissionacrosstheInternetorthecompressionofmovingvideoimagesinvideotelephonyandvideoconferencing．Videotelephonyisoneofthecurrentcrossoverareasthatemploybothcomputergraphicsandclassicalimageprocessingtechniquestotrytoachieveveryhighcompressionrates．AllthisispartofaninexorabletrendtowardsthedigitalrepresentationofimagesIndeedthatmostpowerfulimageformofthetwentiethImageprocessingischaracterizedbyalargenumberofalgorithmsthatarespecificsolutionstospecificproblems．Somearemathematicalorcontext-independentoperationsthatareappliedtoeachandeverypixel．Forexample，wecanuseFouriertransformstoperformimagefilteringoperations．Othersare“algorithmic”—wemayuseacomplicatedrecursivestrategytofindthosepixelsthatconstitutetheedgesinanimage图像处理不是一步就能完成的过程。可将它分成诸多步骤，必须一个接一个地执行这些步骤，直到从被观察的景物中提取出有用的数据。依据这种方法，一个层次化的处理方案，该图给出了图像处理不同阶段的概观。图像处理首先是以适当的但不一定是光学的采集系统对图像进行采集。在技术或科学应用中，可以选择一个适当的成像系统。此外，可以建立照明系统，选择最佳波长范围，以及选择其他方案以便用最好的方法在图像中获取有用的对象特征。一旦图像被检测到，必须将其变成数字计算机可处理的形式，这个过程称之为数字化。随着交通问题的日益严重，智能交通系统应运而生。汽车牌照自动识别系统是近几年发展起来的计算机视觉和模式识别技术在智能交通领域应用的重要研究课题之一。课题的目的是对摄像头获取的汽车图像进行预处理,提出了车牌预处理、车牌缘检测的频率分析法。从经过边缘提取后的车辆图像中提取车牌特征分析处理,从而初步定出车牌的区域，再利用车牌的先验知识和分布特征对车牌区域二值化图像进行处理，从而得到车牌的精确区域。在图像中，对已知的干扰进行校正也是不可少的，比如由于光学聚焦不准，运动模糊，传感器误差以及图像信号传输误差所引起的干扰。在此还要涉及图像重构技术，它需要许多间接的成像技术，比如不直接提供图像的射线断层技术等。一套完整的处理步骤对于物体的分析和识别是必不可少的。首先，应该采用适当的过滤技术以便从其他物体和背景中将所感兴趣的物体区分出来。实质上就是从一幅图像（或者数幅图像）中抽取出一幅或几幅特征图像。要完成这个任务最基本的工具就是图像处理中所使用的求均值和边缘检测、单的相邻像素分析，以及复杂的被称为材质描述的模式分析。物体的一个重要特性就是它的运动性。检测和确定物体运动性的技术是必不可少的。随后，该物体必须从背景中分离出来，这就意味着具有同样特性和不同特性的区域必须被识别出来。这个过程产生出标志图像。既然已经知道了物体精确的几何形状，就可以抽取诸如平均灰度值、区域、边界以及形成物体的其他参数等更多的信息。这些参数可用来对物体进行分类，这是许多图像处理应用中至关重要的一步，比如下面一些应用：在一个显示农业地区的卫星图像中，想要区别出不同的果树，并获取参数以估算出成熟情况并监测害虫情况；在许多的医学应用中，最基本的问题是检查病理变化，最典型的应用就是染色体畸变分析；印刷体和手写体识别是另一个例子，图像处理一出现，人们就开始对它进行着研究，现在依然困难重重。人们希望能了解得更多一些，也就是试图理解所读到的内容。这也是图像处理的最后一个步骤，即理解所观察到的景象。当我们使用视觉系统时，实际上已或多或少无意识地在执行这个任务。我们能识别不同的人，可以很轻易地区分出实验室和起居室，可以观察车流以便安全地穿行马路。我们完成这样的任务而并不了解视觉系统工作的奥秘。长久以来，图像处理和计算机图形学被看做两个不同的领域。现在，人们在这两个领域中的知识都有了极大的提高，并可以解决许多复杂的问题。计算机图形学