分析案例教案rm draftreport

UndergraduateProjectReport[LeapMotionBasedHand-writtenTextRecognitionSystem] [GAO [Internetof QMStudent BUPTStudentNo. ProjectNo. DateTableof Chapter1: Chapter2: puterInction Leap Inction Motiontracking Image OpticalCharacterRecognition Gesture Chapter3:Designand Collect Image Median Image Gesture Remove Detect Chapter4:Resultsand Chapter5:ConclusionandFurther Risk EnvironmentalImpact Hand-writtenTextRecognitionandSomatosensoryInctionare2importantofVirtualReality,andVirtualRealitywill ethemostimportantmodeof Inction.Mostpreviousworkarefocusontheirrespectivefields.ItmeansthattherearefewcooperationbetweenHand-writtenTextRecognitionandSomatosensoryInction.Therefore,theirrecognitionaccuraciesonlycanrelyontheirrespectivealgorithmstoimprovetherecognitionThispaperpresentsaHand-writtenTextRecognitionsystembasedonLeapMotionwhichisasomatosensorydevicewithhighprecision.ThesystemcombinedtheofHand-writtenTextRecognitionandgesturerecognition.Specifically,throughtrainingthenewhand-writtenlanguagelibraryandapplyingtheofimageprocessingandgesturerecognition,thissystemnotonlyachievedarobustalgorithmtoimprovehandwritingrecognitionaccuracy,butalsostrengthenedthecapacitytohandlecomplexgestureforthesomatosensoryequipment.Thepaperhas5sections.Chapter1isIntroductionwhichintroducesthetechnicalcontext,forinstance,theconceptandfeaturesofLeapMotion,gesturerecognitionandTesseractOCREngine.Inthesection,theworksIhavedoneandthefeaturesofthisprojectalsoarepresented.Chapter2isBackground,whichdescribestheknowledgethatrelatestothisproject,forexample,Human-ComputerInction,SomatosensoryInction,C++programminglanguage,theAPIofLeapMotion,imageprocessing,andOpenCV.Chapter3istheDesignandImplementation,whichintroducesspecificallythealgorithmdesignandsystemimplementation,suchashowtogetuserinput,howtoprocessuserinput,howtotrainlanguagelibrary,howtousegesturerecognitiontoimproverecognitionaccuracy.Chapter4isResultandDiscuss,whichshowstheresultofmyworks,andadvantagesanddisadvantagesofthesystem.Chapter5isConclusionandFurtherWork,whichconcludestheworkIhaveachieved,andintroducestheworkwillbeenhancedinthefuture.Keyword：LeapMotion,Hand-writtenTextRecognition，Imageprocessing，gesturerecognition,TesseractOCREngine(translationof 2個(gè)重要的虛擬現(xiàn)實(shí)技術(shù)，并且虛擬現(xiàn)實(shí)將會(huì)是最主要的人機(jī)交 展示了一種基于LeapMotion這一高精度體感交互設(shè)備的手寫(xiě)文字識(shí)別系統(tǒng)。這個(gè)這篇5個(gè)章節(jié)：第一章是介紹，這個(gè)部分簡(jiǎn)要的介紹了這個(gè)項(xiàng)目的技術(shù)背景,比如LeapMotion的概念和特點(diǎn)，TesseractOCR引擎的概念和特點(diǎn)，以及手勢(shì)識(shí)別技術(shù)的概念像處理的相關(guān)知識(shí)，OpenCV和LeapMotion的API。第三章是設(shè)計(jì)，這個(gè)部分會(huì)詳果,優(yōu)點(diǎn)，和缺點(diǎn)。第五章是總結(jié)和未來(lái)工作，介紹我做過(guò)的工作，以及未來(lái)可以調(diào)高的工TesseractOCRChapter1:VirtualRealityisanidealmodeof puterInction.Itprovidesmoreefficientinctiveexperience,anditwillmakeanimportantinfluenceinhumanlifeinthefuture.Hand-writtenTextRecognitionandSomatosensoryInctionare2importantofVirtualReality.Withalongtimedevelopment,thetechnologyofprintedcharacterrecognitionhas advantaged.TherearemanyOCREnginesprovidehighaccuracyofrecognitionforprintedcharacter,likeTesseractOCREngine.Now,somatosensorydevicesandgesturerecognitiontechnologyareverypopular,LeapMotionisasomatosensorydevicewhichcanrecognizeandtrackhands,fingersandfinger-liketoolswithhighprecisionandtrackingframerate.Itcanreportdiscretepositions,gestures,andmotionLeapMotionControllertracksall10fingersupto1/100thofamillimetre,andithaveafieldofviewofabout150degreesandaZ-axisfordepth,whichmeansyoucanmoveyourhandsandfingersin3D,justlikeyoudointherealworld.[1]However,theaccuracyofrecognitionforhand-writtencharacterislow.Andthesomatosensorydeviceonlyrecognizesomesimplegestures,likecircle,swipe,keytap,andscreentapTherefore,IdesignedaHand-writtenTextRecognitionsystembasedonLeapMotiontoenhancetheaccuracyofHand-writtenTextRecognitionandtheabilityofhandlingcomplexgestureforLeapMotion.Thissystemcombined3coreincludingOCR,imageprocessingandgesturerecognition.Inthisproject,using’sTesseractOCREnginehandlesOCR,andinvokingOpenCVoperatesimageprocessing,andutilizinggesturerecognitionimprovestheaccuracyofOCR.Particularly,firstLeapMotionrecordsuser’sinputthatincludespositionsandtimestamps,andsavestheinputasapicture.ThenOpenCVwasusedtoprocessthepicture.Forexample,usingMedianfilterprotectstheimageedge,andsmoothiesnoises,invokingcvDilate()removesuselessthincurves,anddeleteduselesscontentsbyresizingthepicture.Afterthat,thesystemmakesthepictureprocessedastheinputofTesseractOCREnginethathasahand-writtentraineddata.TheoutputofOCREngineistheinitialresult,iftheinitialresultisaconfusingletter,itwillbere-recognized,throughgesturerecognitionbasedonthepositionsandtimestamps.Chapter2:puterInctionItisastudythatresearchestheinctiverelationshipbetweensystemandhuman.Thesystemcanbevariousmachinesandsoftware.Humanandcomputeruseaparticularlanguageandinctivemodetoachieveinformationexchange.puterInctionisanimportantfactortothefriendlinessofacomputersystem.ThefunctionsofHCImainlyrelyoninput/outputexternaldevicesandrelativesoftware.ThemainapplicationsofHCIincludecontrollingrelativedevices,understandingandexecutingusers’variouscommandsandrequires.Earlyinctivefacilitiesarethekeypadanddisy.Operatorsthroughthekeyboardinputthecommand.Commandsareexecutedimmediayaftertheoperatingsystemreceivestheordersanddisysresultsonthescreen.Commandsmayhavedifferentformats,buttheinterpretationofeachcommandisclearandunique.Withthedevelopmentofinformationtechnology,patternrecognitions,likevoicerecognition,opticalcharacterrecognitionandgesturerecognition,havegothugeprogress,whichprovidesavarietyofinctivemode.Sofar,HCIhasexperiencedthefollowingManualJobControlLanguageandInctiveCommandGraphicalUserInterfaceInligentinctionwithmultichannelandSomatosensoryInSomatosensorytechnologyhasmadeitpossiblethatusingbodymovementsdirectlyinctwiththesurroundingequipmentortheenvironment,withoutusinganycomplicatedcontroldevice.Itcanletpeopleinctefficientlyandlivelywiththesystemandcontent.Forexample,whenyoustandinfrontofaTV,ifthereisasomatosensorydevices,likeKinect,candetectyourhandmovements,wecouldcontrolevisionfast-forward,rewind,pause,andterminationandotherfunctions,throughourhandmovements,likeup,down,leftandright.Itisappropriateexampletosomatosensorycontrolperipheraldevices.Ifweuseourbodymovementstocontrolcharacter'sreaction,directly,yerscangetimmersivegamingexperience.OtherSomatosensoryapplicationsinclude3DVirtualReality,healthcare,motiondetectionandsoon.C++programminglanguageisageneral-purposeprogramminglanguage,whichdevelopedbasedonLanguageC.C++supportsmultipleprogrammingparadigms,likeobject-orientedprogramming,genericprogrammingandproceduralprogramming.Itappliedinmanyfields,likesystemdevelopment,enginedevelopment.Anditisoneofthemostpopularandpowerfulprogramminglanguage,becauseitsupportsclass,encapsulation,andoverload.RelationshipwithLanguageClanguageisthebasisofC++,C++andClanguagearecompatible,inmanyClanguageisastructuredlanguage,itfocusonalgorithmsanddatastructures.ThedesignprincipleofCprogramishowaprocessobtainstheoutput(orimplementation(things)control)fromaninput.ThecoreofC++ishowtoconstructanobjectmodel,whichcanfitthecorrespondingproblem,sothatyoucangetoutputorimplementation(things)controlbyobject'sstateinformation.Insum,thebiggestdifferencebetweenCandC++isthatthinkingthattheysolvetheproblem,isnottheC++isasefficientasCC++supportsvariousprogrammingstyles,likeproceduralprogramming,data ion,object-orientedprogramming,andgenericprogrammingC++programmingdonotneedcomplexprogrammingC++programminglanguageisflexible.Ithasabundantoperators,datastructure,andstructuredcontrolstatements.Andithastheadvantagesofhigh-levelprogramminglanguageandassemblerlanguage.Forexample,C++programsareefficient,readable,andportable.Generallyspeaking,C++languagehas2mainfeatures,oneiscompatibility,theotheroneistheobject-orientedapproach.IthaslanguageC'sfeatures,likesimple,efficient,andexpandsC’typesystem,soC++saferthanC++introducesobject-orientedconcepts,whichmakethedevelopmentofinctiveapplicationismoresimpleandfast.ManyexcellentprogramframeworklikeBoost,Qt,MFC,OpenCVisusedThecorrectnessofcomplexC++programsisquitedifficulttoC++hasabundantdifferentstandards,soproducingareasonably pliantC++compilerhasproventobeadifficulttask.TesseractisaOCRenginewhichmaybehasthehighestaccuracy.TesseractOCRenginecanreadprintedtextofover60languages.TesseractOCRenginewasdevelopedbyHPlabin1985.Until1995,itwasoneofthetop3OCRenginesaroundtheworld.However,therewaslittleworkdoneonit,between1995and2006,becauseHPdecidedtoabandontheOCRbusiness.Inlate2005,HPreleasedTesseractforopensource.Sincethattime,Tesseracthas ethemostpopularandaccurateopensourceOCRengineavailable.[2]LeapLeapMotionisasomatosensorydevicewhichcanrecognizesandtrackshands,fingersandfinger-liketoolswithhighprecisionandtrackingframerate.Itcanreportdiscretepositions,gestures,andmotiontoo.InctionLeapMotionhas2opticalsensorsand1infraredlightsensor.Throughthesesensors,LeapMotionhasafieldofviewofabout150degrees,andtheeffectiverangeextendsfromaround25to600milimetters.Inthisperception,LeapMotioncanrecognizeandtrackthemovementofhandsandfigures.Forcollectingdata,theLeapMotionsystememploysaright-handedCartesiancoordinatesystem.TheoriginisthecenterofthetopoftheLeapMotionController.Thex-andz-axeslieinthene,withthex-axisrunningparalleltothelongedgeofthedeviceandpointingtotheright.[3]They-axisisperpendiculartothedevice,withpositivevaluesincreasingupwards.Thez-axispointtotheFigure1TheLeapMtionright-handedcoordinateTheLeapMotionAPImeasuresphysicaltieswiththefollowingFigure2TheunitsofphysicaltitiesmeasuredbytheLeapMotionMotiontrackingInthefieldofview,LeapMotiontracksthemovementofhandsandfinger,anditrecordsandupdatesthedatainformofframe.Thedatathateachframecontains,includes:ThelistandinformationofallThelistandinformationofallThelistandinformationofThegestureandLeapMotionControllerdistributesauniqueIDtoeachobject.AndtheIDsneverchange,whentheobjectsstaywithinthefieldofview.BasedontheIDs,wecaninquireinformationabouteachTheLeapMotioncontrollercanrecordandprovideinformationabouteachfingeronahand.Forexample,theinformationincludesfinger’sname,long,position,direction,andspeed.Andtherearemanyfunctions,likefingerType(),fronmost(),length(),tipposition(),whichcangettheFigure3ThemodeloffingerstrackedbyLeapLeapMotionprovidesAPIstorecognizecertainmovementpatternsoffingersortoolaswhichcouldindicateauserintentorcommand.TheLeapMotionsoftwarepresentsgesturesinaframethatisthesamewayitreportsothermotiontrackingdatalikefingersandhands.[3] ScreenTapGesture,andSwipeGesture.ThefollowingmovementpatternsarerecognizedbytheLeapMotionFigure4Circle–AfingertrackingaFigure5Swipe–Along,linearmovementofahandanditsFigure6KeyTap–AtapmovementbyafingerasiftapakeyboardFigure7–AtapmovementbythefingerasiftapaverticalcomputerImageImageprocessingreferstotheinformationtechnologythatremovesnoise,andenhances,restores,segments,extractsfeaturesforimages,throughcomputer.Itcanimprovethequalityofimages,forexample,enhancingthelightofimages,transformingcolour,enhancingorrestrictingcertaincontent,makinggeometrictransformationforimages.Itcanextractcertainfeaturesorspecificinformationcontainedintheimage.Thefeatureinformationfacilitatecomputerysisoftheimage.Extractingfeaturesmayincludemanyaspects,suchasthefrequency,grayscaleorcolorcharacteristics,boundarycharacteristics,regionalcharacteristics,texture,shapefeatures,topologicalfeaturesandrelationshipstructure.Itcanfacilitateimagestorageandtransmissionthroughtransforming,encodingandcompressionimageOpticalCharacterRecognitionOpticalcharacterrecognition(OCR)isthetechnologyandprocesswhichconversestheimagesoftypewrittenorprintedtextintomachine-encodedtext.OCRtechnologyrelatestopatternrecognition,artificialinligenceandcomputervision.[4]TheindexesusedtomeasuretheperformanceofanOCRsystemincluderejectionrate,friendlyerrorrate,recognitionspeed,userinterface,productstability,easeofuseandfeasibilityOCRsoftwareoften"pre-process"imagestoimprovethechancesofsuccessfulrecognition.Thefollowingtechniquesof"pre-processes"couldreducethedifficultyoffeatureextractionalgorithm,andcanimprovetheaccuracyofrecognitionBinarization–itcanseparatethetextfromthebackground,anditimprovethespeedoftextrecognition.Weneedconvertanimagefromcolororgreyscaletoblack-and-white.NoiseRemoval–theimagesisnotalwaysgood,whichmeanthatthereisalotofnoise,sotheimagesshouldberemovednoisebasedonthenoisesfeatureofimagestoimprovetheaccuracyofrecognition,beforetheOCRenginerunsrecognitionprocessingforthecharacters.Tiltcorrection–becausetheinputtedimagesarealwaysdeclining,itisnecessarytodetectandcorrectimages’directionTextfeatureextraction–itisthecoreofOCR,becauseitdirectlyaffectstheresultofOCR.Andthefeaturesisthebasisofrecognition.Thefeaturescanbedividedinto2categories:oneisstatisticalfeature,suchastheproportionofblackandwhitepointwithinthewordregion.Whenstatisticalfeaturematchingisrun,thebasicmathematicaltheoryissufficient.Theothercategoryisstructurefeature,likeCharacterstrokesendpoints,thenumberandlocationoftheintersection,lines,closedloops,linedirection.Itneedsspecificmatchingmethodstomatchfeatures.CharacterBecausethetextfeaturesaredividedintostatisticalfeatureandstructurefeature,therearetwobasicapproachesofcharacterrecognition,whichproduceacorrectcandidatecharacters.Statisticalrecognisersarebasedonthestatisticalfeature,liketheradiobetweenblackpixelandwhitepixelwithinatextregion.Whenthetextregionisseparatedseveralregions,thecombinationofsingleradioofblack/whitepointsmakesupanumericvectorspace.Mathematictheoriesareusedtomatchfeatures,inthestatisticrecogniserStructurerecognisersusestructurefeatureslikelines,closedloops,linedirection,andlineintersectionstorecognisecharacters.[5]Differentstructurefeatureneeddiversematchingmethod.Post-SinceOCRrecognitionratecannotreachonehundredpercent,orwewouldliketostrengthenconfidenceandaccuracyofrecognition,orevenwewanttoaddthedebuggingfeaturestohelpcorrect, esanecessarymoduleofOCR.“Afterwordprocessing”isanexample,basedonthebeforeandafterthewordstofindthemostlogicalintherecognizedcandidates,todocorrectionUpdateThecorrectedtextsandtheirfeaturescanbeaddedtothedatabase.Throughupdatingdatabase,theaccuracyofTesseractOCRenginecanstrengthentheconfidenceandaccuracywhenitrecognizethesametextGestureBroadlyspeaking,gesturereferstothemovementofhandsorfingers.Whetheroperatingobjectorcommunicating,gesturesalwayspresenttheintentionofpeopleGesturerecognitionisatechnologythatconvertsgesturestocomputercommandsthroughprocessthegesturesGesturerecognitionisbasedonauser'sgesture,anditidentifythemeaningofthemovement.Itdirectlyasacomputerinputdevice,andthe puterInctionnolongerneedotherintermediateequipment.Peoplecandefinesomesimplegesturetocontrolsurroundingmachine.Theexecutionofgesturesisadynamicprocedure,forinstance,thechangeofpositionanddirectionofhandinspace.Sothefeaturesofagestureshouldbedescribedfrom2aspects:timeandBasedonthetime-varyingcharacteristicsofgestures,gesturerecognitioncanbedividedinto2classes:staticgesturerecognitionanddynamicgesturerecognition.Theresearchpointofstaticgesturerecognitionistheposturesofhandsandsinglehandshape.Thatmeansitonlyneedtorecognizethefeaturesofhandshape.Forexample,inAmericanSignLanguage,theshapeoffingerspresentstheEnglishletter.Theobjectofdynamicgesturerecognitionareaseriesofconsecutiveactions.Forexample,agesturerecognitiondeviceusesappropriatealgorithmtorecognizethemeaningofthewholeaction.OpenCV(OpenSourceComputerVision)isacross-tformlibraryofprogrammingfunctionsmainlyaimedatreal-timecomputervision.[6]OpenCVislightweightandefficient,becauseitiswritteninC++anditsprimaryinterfaceisinC++,butithasfullinterfacesinPython,Java,Chapter3:DesignandCollectingForcollectinginputfromLeapMotionController,firstlyaControllerobjectthatconnectstothedeviceandaListenerobjectthathandlesevensandserver,werecreatedinthemain()function,andthecall-backfunctionswereoverriddenforthissystem.Thenthelistenerobjectwasaddedtothecontrollerobjecttolistenandresponsetheevensofthecontroller.Afterthat,theeventslistenedbylistenerweredeclared.Theinformationabouttheuserinputswascollectedasaframeformat.TheonFrame()callbackfunctionwasoverriddentogettheappropriateinformation.Becausethemotionofoneuser’sfingerisinput,onlythepositionsofthemostfrontfingeroftheuserwerecollected.Thepositionisa3Ddataincludingx,y,andz.thex-axisandy-axisformanethatsimulatesapapertorecordthetrackofuser’sfinger.Andthevalueofz-axisaffectsthethicknessofcurves,whichmakethetrackshownonthewindowlookslikewrittenwithapen.Inthisway,theinctioninterface esfriendlier.Andthevalueofz-axisdecidesthatthesystemwhetherrecordsthepositionoffinger.Forrealtimeshowingthetrackofuserinput,manyOpenCVfunctionswereinvokedintheonFrame()function.Forexample,cvLine()wereinvokedtoconnectcurrentpointoffingerwithlastpointtomakeacurve,andcvShowImage()showsthecurvesonacertainwindowGestureswereusedtoachievecertaincommands.IfTYPE_SWIPEgesturewasrecognized,allofthetracksshownonthewindow,andthepositionsrecordedwillbedeleted.IfTYPE_KEY_TAPgesturewasrecognized,thetrackswillbesavedasapicture.Thenthesystemexecutesimageprocessingtothepicture.AndOCRenginewillbeusedtorecognizethecharactersavedintheprocessedimageImageImageprocessingcanimprovetheaccuracyofOCRandtheeffectiveofrecognition,becauseimageprocessingcanremovenoiseandenhanceimagefeatureThereare3imageprocessinginthisMedianInimageprocessing,suchasedgedetected,usuallyitneedsanoisereduction.Medianfilterisacommonstepinimageprocessing,anditisparticularlyusefultoprocessspecklenoiseandpepperMedianfilterisanonlinearsmoothingtechnique,whichisusuallyusedtoprotectedgeinformation.Specifically,itusethemedianofalltheneighbourhoodwindowpixeltorecethepixelofapoint.ItisInthissystem,medianfilterfunctionisprovidedbyOpenCV,anditwasinvokedtosmooththeinputAim:deleteuselessthinSincerealtimeshowthetrackandpositionofuser’sfingerinthecertainwindow,therearelotsofuselessthinlinesavedinthepicture.SothissysteminvokedOpenCV’sdilatefunctiontoremovetheuselessthinlineFigure8BeforeFigure9AfterImageForreduceuselesscontainsandstrengthenstructurefeature,thesystemresizedtheinputtedFirstly,traversaleverypixeloftheimage.Thencalculateandrecordthesumofpixelofeverycolumnandrow.Afterthat,comparethesumofeverycolumnwithaparticularvalue,thepixelofwhitemultiplythenumberofcolumn,columnbycolumnfromlefttoright.Whenthe2valuesarenotsame,thepositionofcolumnistheleftedgeofresizedimage.Usingthesamemethodtomakesuretherightedge,topedge,andloweredge,butthesequenceofcomparisonisfromrighttoleft,fromtoptobottom,andformbottomtotop,respectively.Finally,usingOpenCV’sresizefunctiontoresizetheAlthoughTesseractOCREngineisthemostaccurateopensourceOCRengine,anditsupportmorethan60language.Butithasn’tanappropriatehand-writtentextlibrary.Thatmeansitisnotgoodatrecognizinghand-writtentext.Thesystemcollected4hand-writtenEnglishalphabetastrainingdatatotrainahand-writtentextlibraryFigure10TrainingFigure11correctingtheGestureItisverydifficulttoaccurayrecognizeeverycharacterthroughusingTesseractOCREngineandthetrainedhand-writtentextlibrary.SothesystemusedagesturerecognitionalgorithmtoimprovetheaccuracyofrecognitionThegesturerecognitionalgorithmincludesthefollowingRemoveLeapMotionisahighlyprecisionsomatosensorydevices.Itcanrecognizemovementoffingerupto1/100thofamillimetre.Andtheupdatefrequencyofdataisupto200framesperminute.SothepositiondatathatcollectedthroughLeapMotionControllerisverylarge,whichdecreasestheprocessefficiency.Duetothehighlyprecision,lotsofuselesspositions,likehandorfingershakinginformation,werealsorecordedintothepositiondata.TheseuselessinformationdirectlyinfluencetheefficiencyandaccuracyofgesturerecognitionInthesesystem,thereisanoisereducingsteptohelpimprovetheefficiencyandaccuracyofgesturerecognition.Particularly,scanningtheoriginalpositiondatacollectedthroughLeapMotionController,exceptthefirstposition,allofthepositionswithadistancetothepreviouspositionislessthan10mm,shouldbedeleted.Thatmeansinthenewpositiondata,thedistancesbetweenanyneighbouringpointsmustbemorethan10Figure12RemoveDetectForrecognizegesture,usingthecharacteristicsofthetrigonometricfunctions,thesystemconvertsthegestureintoan8-directiongesturesequence.Particularly,everylinesegmentbetween2positioninthenewpositiondataintooneof8-direction:up,right-up,right,right-down,down,left-down,left,left-up,andusing1to8torepresentthem.Inthisway,thepositiondataconvertedtoadirectionset.Figure138-directioncoordinateThisstepconvertsthe8-directionsgesturesequencetoamoresimplepresentation(e.g., Inthisway,thesystemcaneasilymatchedtotheFigure14Troughimageprocessing,andtraininghand-writtentextlibrary,mostofthehand-writtencharacterscanberecognizedaccuray.But,therearestillsomecharactersareeasilyconfused,becauseitsstructurefeaturesaretoosimilartoidentify,like‘c’and‘e’.ThesystemusedgesturerecognitiontoimprovetheresultofTesseractOCREngine.Forexample,‘c’and‘e’areeasilyconfusedbyTesseractOCREngine,butitsfirstdirectionalwaysaredifferent,thefirstdirectionof‘e’onlycanbe2,or3,or4,whilethefirstdirectionof‘o’isalwaysnot2,or3,or4,sowecanusethisfeatureofgesturetorecognize‘c’or‘e’.Usingthegesturesequence,wecanalsorecognizeothereasilyconfusedletter,like‘o’and‘a(chǎn)’EvenwecancalculatethedistanceofgesturesequencetorecognizewhichletterismoreGestureChapter4:ResultsandUsingimageprocessing,gesturerecognition,andTesseractOCREngine,thesystemdesignedandimplementedarobustalgorithm,whichmakesthesystemcanaccurayrecognizethehand-writtenlettersinputtedbytheuserthroughLeapMotion.ThesystemprovidesbasicinformationaboutthestateofLeapMotionandrecognitionresultinacommandwindow.Anditcanreal-timeshowsthetrackofuser’sfinger,whichhelpstheusermoreeasilyinput.Itcanalsodirectlyandaccurayrecognizesmostofuser’sinputs,becausethesystemhastrainedahand-writtenEnglishletterlibraryforTesseractOCREngine.Toidentifysomeeasilyconfusedletter,like‘e’and‘c’,thesystemcanaccurayidentify,byrecognizingthefeaturesofFigure15SystemFigure16therecognitionofhand-writtenletterFigure17therecognitionofhand-writtenletterFigure18therecognitionofhand-writtenletterLetter‘c’inputedbyuseriseasilyrecogniz