Introductory Chapter: On Fingerprint Recognition

Fingerprint recognition is the procedure of comparing known and unknown fingerprints to prove that the it is from the same person or not [8] ... Home>Books>BiometricSystemsOpenaccessIntroductoryChapter:OnFingerprintRecognitionWrittenByMuhammadSarfrazPublished:February10th,2021DOI:10.5772/intechopen.95630DOWNLOADFORFREEShareCiteCitethischapterTherearetwowaystocitethischapter:1.ChoosecitationstyleSelectstyleVancouverAPAHarvardIEEEMLAChicagoPlaceholderCopytoclipboard2.ChoosecitationstyleSelectformatBibtexRISDownloadcitationIntechOpenBiometricSystemsEditedbyMuhammadSarfrazFromtheEditedVolumeBiometricSystemsEditedbyMuhammadSarfrazBookDetailsOrderPrintChaptermetricsoverview573ChapterDownloadsViewFullMetricsDOWNLOADFORFREEShareCiteCitethischapterTherearetwowaystocitethischapter:1.ChoosecitationstyleSelectstyleVancouverAPAHarvardIEEEMLAChicagoPlaceholderCopytoclipboard2.ChoosecitationstyleSelectformatBibtexRISDownloadcitationImpactofthischapterIntechOpenDownloads573TotalChapterDownloadsonintechopen.comCitationsCitations2CitationsAdvertisementAdvertisementAuthorInformationShow+MuhammadSarfraz*DepartmentofInformationScience,CollegeofLifeSciences,KuwaitUniversity,SabahAlSalemUniversityCity,Shadadiya,Kuwait*Addressallcorrespondenceto:[email protected];,hawra.alhussain@grad.ku.edu.kw1.IntroductionThebiometricphrasemeanslifemeasurementintheGreeklanguage[1].Thatisanytechniqueusedformeasuringbiologicalinformationforrecognitiongoalscalledbiometric.Therearevariouskindsofbiometricsbeingused,theseincludeFingerprint,Face,Speaker/Voice,Infraredthermogram(facial,handorhandvein),Gait,Keystroke,Odor,Ear,Handgeometry,Retina,Iris,Palmprint,Signature,DNA,Knucklecrease,Brain/EEG,Heartsound/ECG.Defininghumansusingbiometriccanevenbebehavioralorphysiologicalbiometrics.Thedifferencebetweenthemisthatbehavioralbiometriccanbeaffectedwiththeprogressofthetimesuchassignature,gait,speech,andkeystrokebutthephysiologicalbiometricareconstantduringhumanlife.Fingerprint,face,iris,andpalmprintsareexamplesofphysiologicalbiometric[2].ABiometricsystemisreliablebecauseitcannotbestolen,borrow,bought,orforgottenlikeapasswordorID[3].Thefingerprintisaphysicalbiometricaspect.Itisusedtoidentifyaperson’sidentityduetoitsuniquenesswherenotwopersonscansharethesamefingerprint.Besides,afingerprintisunchangeablewithtimeandcanbeeasilyrecognizedduringthewholelifeoftheindividual.Thefingerprintisanimpressionormodelofribsandvalleysatthetopofaperson’sfingers.Figure1showsafingerprintpattern.Fingerprintrecognitionistheautomaticprossesofcomparingsavedfingerprintpatternwiththeinputfingerprinttodeterminehumancharacters.Althoughfingerprintrecognitionwasdeployedfromdecadeitbecameoneofthemostcommonbiometricnowadays.Thefingerprintidentificationsystemisacheapbutsolidmechanismatthesametime.Moreover,it’sasimplewaytoidentifyhumansspeedilyandaccurately[4].Manyapplicationsappliedfingerprintrecognitionsuchasthemilitary,judiciary,health,teaching,civicserving,mobilesandlaptoplog-in,andmanymore.Moderntechniquesandapproachesareusedrecentlyasasubstitutedofoldinktocapturethefingerprint.Thesetechnologiesdifferintermsofaccuracy,effectiveness,speed,advantages,andchallenges[5].Thischapterdiscusses,comparesandanalysesseveralauthorswork[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]regardingthefingerprintrecognition.Figure1.Afingerprintmodel.Theremainingofthechapterisorganizedasfollows.Section2isanoverviewoftheliteraturesurveywithcomparativeresearch.Section3dealswithadetailedanalyticalstudyoftheliteraturereview.Atlast,futuredirections,recommendations,andconclusionarepresentedinSection4.Advertisement2.LiteraturesurveyFingerprintrecognitionistheprocedureofcomparingknownandunknownfingerprintstoprovethattheitisfromthesamepersonornot[8].Today,manyapproaches,techniques,andsystemsareusedtomatchfingerprintsandsolverelatedproblems.Thissectionisfocusedonanalyzingandcategorizingdifferentauthor’sworkinthefingerprintrecognitionarea.Table1providesasummaryofvariouspapersinthecurrentliterature.FirstcolumndeterminestheReferenceofthepapersbyauthornamesandyearofpublication.Secondcolumngivesthesummaryoftheworkinthecorrespondingpaper,andthethirdcolumndescribestheimplementedapproachesusedtosolvefingerprintrecognitionissues.Theauthornamesandtheyearofpublicationwillbeusedasanidentifierfortherestofthetablesinthechaptershowingotherdetailsofthereferredliterature.ReferenceBriefsummaryApproachesadopted[8]Explainsdifferentbiometricsstructuresthatareusedforcertificationandrecognitionpurposewithsubmittingtheiradvantagesanddisadvantages.Knowledge-basedapproachTokenbasedapproachBiometricbasedapproach[4]Ageneralexplanationofvarioustypesoffingerprintrecognitionsystemsandpatternsdependingontheminute-basedtechnique.FocusedonPatternrecognition,wavelet,andwaveatommechanisms.Complicationsrelatedtothewaveatommethodarestudied.HistogramEqualizationBandpassFilteringGaborFilteringBinarizationandThinning2DFourierTransformWaveletbasedTransformationWaveatomTransformandMCSoptimizationalgorithm[20]Explainsthedifferencesbetweenvariousfingerprintmatchingtechniquesparticularlylocalminutiae-basedmatchingalgorithms.Itprovidesanexperimentaboutfingerprintidentificationandauthenticationusingtheminutiae-basedmatchingmethodwithanalyzingtheoutcomes.topologyoflocalstructuretypeofconsolidationusageofadditionalfeaturesminutiaepeculiaritiesparameterlearning.[23]Discusesfingerprintauthenticationusingminutiaeextractiontechniqueandcoveringallrelatedsystemsandprocesses.LoadimageHistogramEqualizationFastFourierTransformationBinarizationRegionofInterestThinningMinutiaeExtractionFalseMinutiaeRemoval[21]Beneficentofminutiae-basedfingerprintverificationsystembysuggestingarouteforthefeatureextractionstepwhichdependsonreexaminingthegray-scaleprofilecanincreasethematchingperformanceby4%.Also,theproposedfeaturerefinementstepthatallocatesclasslabelsforevery31qmintiaewillimprovetheperformanceby3%.Bothstepswilldevelopthewholefingerprintverificationsystembe8%.Sequentialapproach[18]ExecutionandassessmentofBiometricImageSoftware(NBIS)forfingerprintrecognitiondevelopedbytheNationalInstituteofStandardsandTechnology(NIST).theNBISisimplementedintheMATLABenvironment.Pre-processingMinutiaeExtractionPostprocessing[17]Designminutiaextractorbyusingdifferenttechniques.Someimprovementsinthethinning,falseremovalapproach,andimagesegmentationisimplementedinthework.SegmentationusingMorphologicaloperationsThinningFalseminutiaeremovalmethodsMinutiamarkingMinutiaunificationbydecompose-ngabranchintothreeterminationMatchingintheunifiedx-ycoordinatesystem[24]Combiningminutiaandcorrelation-basedapproachestoevolveanautomaticfingerprintrecognitionsystem.Byusingthishybrid,theperformanceoftheminutiaealgorithmisgrown.MinutiaeExtractionPost-processingMinutiaeMatchingFilteringFeatureVector[2]PresentFingerprintRecognitionusingtheMinutiaScoreMatchingmethod(FRMSM).ItimplementsBlockFilterforfingerprintthinning.Also,itcompareswithavailablealgorithms.ThinningImagebinarizingNoiseremoval[1]Asummaryofseveralbiometricstechniquesaswellasexplainingtheunimodalandmultimodalwiththeirprosandcons.SensormoduleMatchingmoduleDecision-makingmoduleFeatureextractionmodule[3]Explainingsomebiometricsanddividingthemtocurrentlyinusebiometrics,limitedusedbiometrics,andunderstudybiometrics.Fusionscheme[15]Analignment-basedminutia-matchingalgorithmhasbeendevelopedtoincreasethespeedandaccuracybyabilitydeterminingthematchesbetweeninputminutiaeandStordonewithouttheneedfordetailedstudy.MichiganStateUniversityandtheNationalInstituteofStandardsandTechnologyNIST9fingerprintdatabaseshavebeenused.Theresultshowsthatthefullverificationprocess takes 1.4 secondsaSunULTRA1workstation.Alignment-basedminutiae-matchingalgorithm[22]Applyingfingerprintidentificationbyemployingagraylevelwatershedprocesstofindouttheridgespresentonaspecificfingerprintimage.Theresultdisplaythatthissystemisaccurateandfastwhenmatching7imagesinthedatabase.ImageacquisitionPreprocessingMinutiaedetectionMinutiaereductionFingerprintmatching[26]DiscussingfingerprintrecognitionbiometricindetailandexplainingdeferenttypesofalgorithmslikenegativeLaplacefilterandthenon-stationaryanalysis,andaflexiblealgorithmwithcalculatingthematchingtestresults.ImageacquisitionPreprocess-ngSegmental-onMinutiadetectionBiometricmatching[10]Developinganovelalgorithmforfingerprintmatchingbasedonlocalstructurestoelicitneighboringminutiaefeatureseffectively.ThepresentedalgorithmistestedonFVC2002andtheresultsshowthereliabilityofthesystem.Noveltopology-basedrepresentationtechnique[9]Mixingthedensitymapmatchingwithminutiae-basedmatchingwherethedensitydatacanbeusedinthematchingprocesstoreduceextrastoringcost.Theoutcomesapprovedthatcombiningbothapproacheswillimproveperformance.RegionestimationOrientationfiledestimationFingerprintenhancementCoarsedensitymapextractionWeightedpolynomialapproximation[12]Anadequatewattopressthetemplatesizewithareductionratioof94%byapplyingtowreductionalgorithmstheColumnPrincipalComponentAnalysisandtheLineDiscreteFourierTransformfeaturereductions.Also,afastminutiae-basedmatchingalgorithmcanbeaccomplishedthrowspectralminutiaefingerprintrecognitionsystemwhichshowsmatchingspeedwith125000comparisonspersecondonaPCwithIntelPentiumDprocessor2.80 GHzand1 GBofRAM.ColumnPrincipalComponentAnalysis(Column-PCA)LineDiscreteFourierTransform(Line-DFT)[25]Novelcorepointdetectionmethodthatusesthedetectionalgorithmtoexaminethecorepointanddeterminelocalframeforminutiaeclosetoit.Thentowfingerprintcorrespondingpointswillbeearnedandusedtomatchtheglobalclassthenmakethefinaldiction.Core-basedstructurematchingalgorithm[7]Newtopology-basedalgorithmstomatchfingerprintandaddressthelocalmatching,tolerancetodeformation,andglobalmatching.Theexperimentoutcomesapprovethattimeandperformanceisimprovedusingthealgorithm.Topology-matchingalgorithm[16]Provideahybridmatchingalgorithmthatmatchesfingerprintsusingminutiaeinputsandtextureinputstogether.Thematchingperformanceimprovedwhentesting2560imagesbycollectingbothtexture-basedandminutiae-basedmatchingscores.hybridmatchingapproach(minutiae-basedrepresentationwithatexture-basedrepresentation)[19]Suggestingridgefeature-basedapproachforfingerprintrecognitionthatprovidesgoodresultsforlow-qualityfingerprintimages.Matchingfingerprintimagesbasedonridgelinefeaturesextractedbyusingcontextualfilteringandtwopassthinning.Histogramapproachisusedtomatchthefingerprint.Theexperimentsshowhowtheperformancedevelopedusingthisapproach.ContextualfilterSinglepassthinningalgorithmImagepreprocessGaborfiltering[13]Novelenhancementalgorithmthatsplittheinputfingerprintimagetosetoffilteredimageswhichwillhelpinproducingorientationfieldandqualitymask.TheevaluationprocessofthealgorithmisdoneonanonlinefingerprintverificationsystemusingtheMSUfingerprintdatabasethatconsistsof600fingerprintimagesandthetestdemonstratesthattheenhancementalgorithmimprovestheperformance oftheonlinefingerprintverificationsystem.GaborfiltersRidgeextractionalgorithmVotingalgorithmOrientationestimationalgorithm[14]Submitafingerprintrecognitionalgorithmdependingonphase-basedimagematching.Whichusesthephasecomponentsin2D(two-dimensional)discreteFouriertransformsoffingerprintimagestoreachstrongfingerprintrecognitionwithalow-qualityfingerprint.Thetestusedagroupoffingerprintimagescapturedfromfingertipswithabadcase.Theresultsshowaneffectiverecognitionperformanceusingthisapproach.2D(two-dimensional)Fouriertransforms[6]Thecorrelation-basedfingerprintverificationsystemusestherichergray-scaleinformationofthefingerprints.Inthebeginning,thesystemchoosesappropriatetemplatesintheprimaryfingerprint,employstemplatematchingtolocatetheminthesecondaryprint,andmatchthetemplatepositionsofbothfingerprints.Thetestdescribestheperformanceofcorrelation-basedfingerprintagainstothersystems.ClassificationoftemplatepositionsElementarydecisionsCombiningelementarydecisions[5]Abriefsummaryoffingerprintmatchingtechniques,systems,andperformanceevaluation.ImagecapturingmoduleFeatureextractionmodulePatternmatchingmodule[11]Itprovidesimportantaspectsoffingerprintrecognition.Asbiometricpattern,ithighlightsadetailedanalysisonthefingerprintconceptualization.Itusesvarioustoolstofindthematchpercentageintheverificationprocess.NegativeLaplacefilterNon-stationaryanalysisofthe shorttimeFouriertransformAnalgorithmtofindthematchpercentageintheverificationprocess.[27]Thispresentsafastfingerprintenhancementalgorithm,whichcanadaptivelyimprovetheclarityofridgeandvalleystructuresofinputfingerprintimagesbasedontheestimatedlocalridgeorientationandfrequency.GoodnessindexoftheextractedminutiaeAccuracyofanonlinefingerprintverificationsystem.Table1.Overviewoftheliterature.Table2showstheaccuracyandperformanceinpercentage.Italsomentionstheidentificationandverificationmeasures.Identificationandverificationarematchingtechniquesforfingerprintrecognition.Intheverification,thepersonenrollshisfingerprinttothesystemandthetempletstoreditinthedatabase.Everytimethepersonaccessesthesystem,hehasenteredhisfingerprinttoverifyhimself.It’saonetoonerelationshipwheretheinputfingerprintiscomparedwiththestoredone.Ontheotherhand,identificationisonetomanyrelationshipsbecausethehumanfingerprintismatchedwiththefingerprintsdatabasetodeterminewhoisthatperson[8].Whiletheperformancemeasuresusedforidentificationdependontheaccuracy,recognitionrate,rankK,etc.,theperformancemeasuresforverificationareFalseMatchRate(FMR),FalseNon-MatchRate(FNMR),FalseAcceptRate(FAR),FalseRejectionRate(FRR),andEqualErrorRate(EER).Theresearchersin[4]describethemeaningoftheauthenticationparameters.FARhappenswhenthesystemrecognizespersonerroneous.ButwhenthesystemrejectsentrytoapprovepersonthatmeanstheFRRishappening.FMRistheamountoffraudassessmentswiththresholdvalue‘T’dividedbythetotalquantityoffraudsimilarities.FNMRisthequantitywithunaffectedcomparisonswiththresholdvalue‘T’dividedbythetotalquantityofopencomparisons.LastoneisEER,itdescribestheerrorrateofthesystem.ReferenceAccuracy(Performance)PerformancemeasuresusedforverificationPerformancemeasuresusedforidentification[8]___[4]_FAR,FRR,FMR,FNMR,ERRAccuracy[20]_FMR,FNMR,EER,ROC,FMR100,FMR1000,ZeroFMRTruepositiverate(TPR),R100,ZeroR,CumulativeMatchCurve(CMC),Accuracy,computationaltime,rankk[23]_FMR_[21]95%(LVQ-basedclassifierontrainingdata)87%(LVQ-basedclassifierontestdata)FAR,GARClassificationaccuracy,[18]_FNMR,FMRReliabilityandquality[17]_FRR,FARQualityandaccuracy[24]_FAR_[2]_FMR,FNMR_[1]_FMR,FNMR,FTC,FTEaccuracy,speed,resourcerequirements,acceptability,andcircumvention.[3]___[15]_FAR,FRRAccuracy,speedMorethan45%_Accuracyandtestingtime.[26]_falseacceptance(FA),falserejection(FR),recognitionrate(RR)Accuracy[10]_EER_[9]_FAR,FRRMatchingtimeandcomputationcost[12]_FAR,EER,GARRecognitionaccuracy,matchingspeedandrobustnesstopoorimagequality[25]_FAR,FRRMatchingtime[7]_FRR,FARMatchingaccuracyMatchingtimeComputingtime[16]_GRA,FARComputingtime[19]98%EER,FAR,FRRMatchingaccuracy[13]__RejectRateRecognitionRate[14]_EER,ZeroFMR,FNMR,FMRAccuracy[6]_FRR,FAR,FNMRTestingtime[5]_EER,FAR,FRR_[11]___[27]___Table2.Accuracyandperformance.Theexperimentalpartsoftheauthor’s[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]areshowninTable3.ItexplainsthetypeofapplicationsandkindofDatabasesused.Thenitshowsthenumberoffingertipsusedtocapturethefingerprintsdatabases,thenumberofimagesresultedfromthefingers,theirresolutionsandformats.Finally,Table4describestheimplementedapplicationtypeandthereasonforusingitbymentioningtheadvantagesanddisadvantagesoftheproposedmethods.ReferenceApplicationDatabaseNo.ofidentitiesTotalNo.ofimagesResolutionImageformat[8]______[4]Fingerprint_____[20]FingerprintFVC3081228__[23]Fingerprint_____[21]FingerprintIBMHURSLEYdatabase269900500dpi_[18]FingerprintFVC200060480__[17]Fingerprint__2__[24]FingerprintBiometricSystemLab(UniversityofBologna-ITALY)Inkandscanner21716856256 × 256 × 256dpi240×240×256dpi_[2]Fingerprint_____[1]FingerprintFaceVoiceInfraredthermogram(facial,handorhandvein)GaitKeystrokeOdorEarHandgeometryRetinaIrisPalmprintSignatureDNAFVC2002FRVT2002NIST2000____[3]FingerprintFaceIrisHandgeometryPalmprintSpeaker/voiceSignatureEarshapeKnucklecreaseBrain/EEGHeartsound/ECG_____[15]FingerprintMSUfingerprintdatabaseNIST9(card1)NIST9(card2)7013501350700900900640X480832X768832X768_[22]FingerprintScannerorinkedimpression_7250X250pixelsTIFandBMP[26]Fingerprintcommercialdatabases40_300x300512DPI_[10]FingerprintFVC20024003200__[9]FingerprintTHUdatabaseFCV20028271006616800320X512_[12]FingerprintMCYTFVC2002-DB2145401740400__[25]FingerprintLivefingerprintdatabase_8000300*300_[7]FingerprintfingerprintdatabaseatUniversityofBologna,Italy211680256 × 256_[16]Fingerprint_1602560__[19]FingerprintNRCFVC2000database_300200 × 200_[13]FingerprintMSU67670640*480_[14]Fingerprint_30330256 × 384_[6]FingerprintFVC2000110880__[5]Fingerprint_____[11]Fingerprint_____[27]Fingerprint_____Table3.Overviewoftheuseddata.ReferenceMethodsusedReasonofapplicationAdvantagesDisadvantages[8]____[4]MinutiaebasedapproachPatternRecognitionApproachWaveletbasedApproachesTocomparethefingerprintpatterns.TheuseofpatternsforauthenticationpurposeUsedonfingerprintpatterntocarryouttheverification.Greataccuracyrate.Imagewithnoiseorencryptedcannotbeused,slowapproachandfailstodeterminerealhumans.Notrequiredfingerprintingorpostprocessing,workintheleastthreelevelsoftexturesplittomakethesystemexcellentanditsfastprocess.[20]Minutiae-basedlocalmatchingCorrelation-basedmatchingtechniquesIndexingalgorithmsComparingtowfingerprintstogainaresultofmatchingornonmatching.Calculatethesimilaritiesbetweentowfingerprintimagesbythecorrelationwithincorresponding.Usedwhenit’simportanttoenterfasttothefingerprinttemplatesforrecognition.Simpleanddistortiontolerance.SimplicityExpensivecomputation,slowanddependontheskinsituation.[23]MinutiaebasedmatchingMinutiaextractedfromfingerprintandsavedinthedatabasethenthematchinghappenedbetweenthestoredandinputfingerprint.Widelyusedandfamiliar.Affectedwiththewetordryskin.[21]minutiae-basedfingerprintverificationsystemResolvethegrayscaleprofileintheneighborhoodofpotentialminutiae.Understandthegraylevelimageproperties.__[18]BiometricImageSoftware(NBIS)UsedforfingerprintrecognitioninMATLABenvironment._Timeconsuming,badperformanceforimages.[17]MinutiaeExtractionTechniqueUsedtoreducedistortionforfingerprintmatching.Reduceexecutiontime._[24]hybridAutomaticFingerprintRecognitionSystem(HybridAPRS)Hybridbetweenminutiaeandcorrelation-basedtechniquestorepresentandmatchfingerprint.Improveeachtechniqueindividually.Improveminutiaalgorithm.improvetheridgealgorithm._[2]MinutiaScoreMatchingmethod(FRMSM)Matchingtheinputfingerprintwiththestoresfingerprintdatabase.__[1]UnimodalbiometricsystemsmultimodalbiometricsystemUsingonesinglebiometricfeature.UsingvariousapplicationstobenefitfromdifferenttypesofbiometricsadvantagesReliabilityduetousethecombinationofdeferentbiometricstrength.Scanneddatabecamenoisy.Varityinthelevelofdifficultyinthedatagainedfromhumans.Theremaybealotofsimilarityinthefeaturessetsoftheusedbiometric.Someindividualsmaynothavethechosenbiometriccrater.Biometricsigncanexposetoforgery.[3]unimodalbiometricsystemsmultimodalbiometricsystemRecognitionusingonlyonebiometriccrater.Recognizepersonusingmorethanonebiometricproperty.Latetoprogressintheperformance.NotuniversalCanbefaceableContainmanynoisesvariationswithintheclass.similaritiesbetweentheclasses[15]Automaticidentity-authenticationsystemUsethefingerprinttoidentifypersonidentity.Itsintendedmainlyforforensicapplicationsaccountforap-proximately$100millionfromtheworldmarket._[22]EdgeDetectionTofindtheridgesexistedinthefingerprintimage__[26]Openalgorithmsystem___[10]MinutiaematchingapproachForcreatingminutiaedescriptor__[9]Densitymapmatchingandminutiae-basedmatchingIdentifythefingerprintridgesdensenessandsparsenessLowstoragecost.majorfactorforfingerprintrepresentation.Noredundancybetweenbothsystems._[12]SpectralminutiaefingerprintrecognitionsystemUsedtorepresentaminutiasetasafixed-lengthfeaturevectorHighspeedoperations.Lowmatchingtime.Suitableforlargescalefingerprintidentificationsystem._[25]Structure-basedmatchingalgorithmsCore-basedmatchingalgorithms__MoreeffectivealgorithmNotsuitableforonlineapplicationsandrequirelongtime.Highlydependsoncorepointdetectionprecision[7]Minutiae-basedmatchingFormatchingthefingerprintstofindthesimilaritiesbetweenthem.GoodmatchingcapabilityThemissingminutiaeshouldbeconsidered.Highcostprocess.Hardtononlineardeformationsoffingerprints[16]Minutiae-basedmatchingalgorithms__Notenoughcorrespondingpointsintheinputimages.[19]Ridgefeature-basedapproachUsestheridgestomatchtwofingers.Needlittleprocessing.Increasematchingaccuracy.Powerfulwithlowqualityfingerprintimages._[13]Onlinefingerprintverificationsystem.__Slow.Failtodevolvetheclarityofridgesstructureforgoodqualityfingerprinttemplet.[14]Phase-basedimagematching_Goodresultswhenusingbadconditionfingertips._[6]Correlation-basedfingerprintverificationsystemTomatchtowfingerprintdependingongraylevelfingerprintimages.Workwellwithbadqualityfingerprintimage._[5]Minutiae-basedmatchingPatternmatching___[11]Fingerprintverificationsystem___[27]Minutiae-basedmatchingPatternmatchingUsestheridgesandvalleystructuresofinputfingerprintimages.Improvesthegoodnessindexandtheverificationaccuracy_Table4.Applicationsusedwiththeadvantagesanddisadvantages.Advertisement3.DataanalysisThissectionanalysesthefingerprintrecognitiondataresultingfromtheliterature[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]surveyinSection2.Ingeneral,fingerprintrecognitionprocessescanbedoneusingmultipleprocedures.First,decomposerawhumanfingerprintsampletocreatedigitpresentationofthesamesample.Onthenextstep,preprocessingisdonefortherawinputimagebyfilteringandimprovingfingerprintimagetoproducesuitableoutputimageforfeatureextractionwhichextractstheuniquefeaturesofthefingerprintfromthedigitalrepresentationsample.Theseextractedfeaturesaresavedinthefingerprintdatabaseasfeatures.Finalstepistomatchtheinputfingerprintwithfingerprinttemplatestoredinthedatabasetofindthesimilarities.Theoutcomeoftheseproceduresisdecidingifthepersonisidentifiedornot[8].Figure2describesthesequenceofbiometricorfingerprintsystem.Thefingerprintproceduresinvolvemanydifferentapproachesandalgorithmsthatareusedtoenhanceandimprovethelowqualityoffingerprintimages.Ifthefingerprintimageisongoodquality,thentherearenoissuesandwillappearwhilematching[4].Table1presentstheapproachesthatareusedbydifferentauthors.Figure3presentsthemostusedapproaches.Differentmatchingapproachesareusedin15paperswhichcanbeconsideredasthecommonlyusedapproaches.Thenminutiaeextractiontechniquesareusedinaround10papers.Postprocessingandhistogramequalizationareusedin2papers.Therearesomeotherapproachesusedonlyonceinsomeofthepapers.Figure2.Biometricorfingerprintsystem.Figure3.Themostusedfingerprintapproachesinvariouspapers.Whenthematchingprocessiscompleted.Correctnessofafingerprintidentificationsystemiscalculatedbyapplyingsomeparameters.Itisusedtomeasuretheperformanceofidentificationandverification.Theperformancemeasuresusedforidentificationdependmostlyontheaccuracy,testingtimeandimagequality.Figure4confirmsthat38%oftheworkusedtheaccuracyasthemainidentificationmeasureandapplieditaloneorinadditiontoothermeasures.Ontheotherhand,themostappliedperformancemeasuresforverificationareFalseMatchRate(FMR),FalseNon-MatchRate(FNMR),FalseAcceptRate(FAR)andFalseRejectionRate(FRR).AsshowninFigure5,approximately36%ofthepapersrelyon(FAR)asaverificationmeasure.Figure4.Theidentificationmeasuresusedinthework.Figure5.Theverificationmeasuresusedinthework.Inthefingerprintrecognitionarea,conductingtestandexperimentsisimportanttoapproveandevaluatethequalityandaccuracyoftheproposedwork.Manydifferentdatabaseshavebeenusedtotesttheperformanceoftheproposedmatchingalgorithms.Thesedatabasesvaryintheirsizes,averagenumberoftempletsandinputfingerprints.Figure6describesthedatabasestypesusedinthestudy.AsnoticedfromTable3,FVC2000andFVC2002databasesareusedinsomepapersbutmostpapersusedtheirowndatabases.Forexample,authorsin[24]usedBiometricSystemLab(UniversityofBologna–Italy).Theuseddatabasescontainaseveralnumberoffingerprintsthatareusedtoproducefingerprintimages.Theseimagesareusedinmatchingstep.Figure7showsthediscerptionoftheuseddatabasescharacteristicsbypresentingthenumberofidentitiesandthenumberofimages.Figure6.Theuseddatabasesinthepapers.Figure7.Useddatabasecharacteristics.Atlast,theevaluationoftheperformanceoraccuracyofthefingerprintverificationsystemareappearingin4papersaspresentedinFigure8.Thefigureshowsthehighestaccuracywith95%andthelowestaccuracywith45%.Figure8.Accuracyandperformancefromtheusedpapers.Advertisement4.ConclusionBiometricsmeanstheautomaticidentificationofapersonbasedonhisbehavioraland/orphysiologicaluniquecharacteristics.Fingerprintbiometricsisanefficient,safe,cost-effective,easytousethetechniqueforidentityverification.Thisstudyprovidesdetailedinformationrelatedtofingerprintrecognitiontechniques.Severalauthor’sworks,relatedtofingerprintrecognitiontechnology,arediscussed,comparedandanalyzed.Adetailedanalysisofvariousstudiesismade.Asafuturework,thereisascopetoimprovetheproblemsrelatedtofingerprintrecognition,specially,theissuesrelatedtothecapturingrowfingerprintbythesensors.Oneoftheinnovationsisthetouchlessfingerprintsensor,whichwillbesufficientforcurrent(COVID-19)situations.Itwilldecreetheneedtotouchthedevices.Thistechniqueisneededtoshowitsreliabilityandefficacyasanalternativetoregularsensors.Relyingonafingerprintrecognitioninadifferentgovernmentdomainsisalsorecommended.ImplementingfingerprintrecognitiontechnologyisnotonlyusefulforGovernment,butotherorganizationsandcommunitiescanalsothinkandmaybenefitbyapplyingfingerprintrecognitiontechniquestoidentify.Forexample,inthehealthsector,itisquiteimportanttousefingerprintrecognitiontoidentifythepersoninjuredinanaccident.References1.Delac,K.,&Grgic,M.(2004).ASurveyofBiometricRecognitionMethods.Proceedings.Elmar-2004.46thInternationalSymposiumonElectronicsinMarine,Zadar,Croatia,2004,pp.184-1932.Ravi,J.,K,R.B.,&Venugopal,R.K.(2009).FingerprintRecognitionusingMinutiaScoreMatching.InternationalJournalofEngineeringScienceandTechnology,Vol.1(2),35-423.MirA.H,Rubab,SandJhat,Z.A.BiometricsVerification:aLiteratureSurvey.JournalofComputingandICTResearch,Vol.5,Issue2,pp67-80.http://www.ijcir.org/volume5-number2/article7.pdf4.Borra,S.R.,Reddy,G.J.,&Reddy,E.S.(2016).Abroadsurveyonfingerprintrecognitionsystems.2016InternationalConferenceonWirelessCommunications,SignalProcessingandNetworking(WiSPNET),1428-1434.https://doi.org/10.1109/WiSPNET.2016.75663725.Subban,R.,&Mankame,D.P.(2013).AStudyofBiometricApproachUsingFingerprintRecognition.LectureNotesonSoftwareEngineering,209-213.https://doi.org/10.7763/LNSE.2013.V1.476.Bazen,A.,Verwaaijen,G.T.,Gerez,S.,Veelenturf,L.P.,&Zwaag,B.J.(2000).Acorrelation-basedfingerprintverificationsystem.ProceedingsoftheProRISC/IEEEworkshop,November30–December1,2000,205-213,ISBN:90-73461-24-37.ChengfengWang,Gavrilova,M.,YuanLuo,&Rokne,J.(2006).Anefficientalgorithmforfingerprintmatching.18thInternationalConferenceonPatternRecognition(ICPR’06),1034-1037.https://doi.org/10.1109/ICPR.2006.2368.Deokar,S.,&Talele,S.(2014).LiteratureSurveyofBiometricRecognitionSystems.InternationalJournalofTechnologyandScience,1(2)9.DingruiWan,&JieZhou.(2006).Fingerprintrecognitionusingmodel-baseddensitymap.IEEETransactionsonImageProcessing,15(6),1690-1696.https://doi.org/10.1109/TIP.2006.87344210.Gao,Z.,You,X.,Zhou,L.,&Zeng,W.(2011).Anovelmatchingtechniqueforfingerprintrecognitionbygraphicalstructures.2011InternationalConferenceonWaveletAnalysisandPatternRecognition,77-82.https://doi.org/10.1109/ICWAPR.2011.601449511.Gonzalez,F.C.J.,Villegas,O.O.V.,Sanchez,V.G.C.,&Dominguez,H.d.J.O.(2010).FingerprintRecognitionUsingOpenAlgorithmsinFrequencyandSpatialDomain.2010IEEEElectronics,RoboticsandAutomotiveMechanicsConference,469-474.https://doi.org/10.1109/CERMA.2010.11712.HaiyunXu,Veldhuis,R.N.J.,Kevenaar,T.A.M.,&Akkermans,T.A.H.M.(2009).AFastMinutiae-BasedFingerprintRecognitionSystem.IEEESystemsJournal,3(4),418-427.https://doi.org/10.1109/JSYST.2009.203494513.HongL.,JainA.(2004)FingerprintEnhancement.In:RathaN.,BolleR.(eds)AutomaticFingerprintRecognitionSystems.Springer,NewYork,NY.https://doi.org/10.1007/0-387-21685-5_714.Ito,K.,Morita,A.,Aoki,T.,Higuchi,T.,Nakajima,H.,&Kobayashi,K.(2005).Afingerprintrecognitionalgorithmusingphase-basedimagematchingforlow-qualityfingerprints.IEEEInternationalConferenceonImageProcessing2005,II–33.https://doi.org/10.1109/ICIP.2005.152998415.Jain,A.K.,LinHong,Pankanti,S.,&Bolle,R.(1997).Anidentity-authenticationsystemusingfingerprints.ProceedingsoftheIEEE,85(9),1365-1388.https://doi.org/10.1109/5.62867416.Jain,A.,Ross,A.,&Prabhakar,S.(2001).Fingerprintmatchingusingminutiaeandtexturefeatures.Proceedings2001InternationalConferenceonImageProcessing(Cat.No.01CH37205),2,282-285.https://doi.org/10.1109/ICIP.2001.95810617.Kaur,M.,Singh,M.,Girdhar,A.,&Sandhu,P.S.(2008).FingerprintVerificationSystemUsingMinutiaeExtractionTechnique.2(10),618.Maddala,Sainath,etal.“ImplementationandEvaluationofNISTBiometricImageSoftwareforFingerprintRecognitionc.”ISSNIPBiosignalsandBioroboticsConference:BiosignalsandRoboticsforBetterandSaferLiving,BRC,201119.MarWin,Z.,&MyintSein,M.(2011).AnEfficientFingerprintMatchingSystemforLowQualityImages.InternationalJournalofComputerApplications,26(4),5-12.https://doi.org/10.5120/3094-424620.Peralta,D.,Galar,M.,Triguero,I.,Paternain,D.,García,S.,Barrenechea,E.,Benítez,J.M.,Bustince,H.,&Herrera,F.(2015).Asurveyonfingerprintminutiae-basedlocalmatchingforverificationandidentification:Taxonomyandexperimentalevaluation.InformationSciences,315,67-87.https://doi.org/10.1016/j.ins.2015.04.01321.Prabhakar,S.,Jain,A.K.,JianguoWang,Pankanti,S.,&Bolle,R.(2000).Minutiaverificationandclassificationforfingerprintmatching.Proceedingsofthe15thInternationalConferenceonPatternRecognition.ICPR-2000,Barcelona,Spain,pp.25-29,Vol.1,doi:10.1109/ICPR.2000.90526922.G.S.Rao,C.NagaRaju,L.S.S.Reddy,&E.V.Prasad.(2008).ANovelFingerprintsIdentificationSystemBasedontheEdgeDetection.IJCSNSInternationalJournalofComputerScienceandNetworkSecurity,Vol.8(12),394-39723.Sharma,M.(2014).FingerprintBiometricSystem:ASurvey.InternationalJournalofComputerScience&EngineeringTechnology,Vol.5(7),743-74724.Youssif,A.A.A.,Chowdhury,M.U.,Ray,S.,&Nafaa,H.Y.(2007).FingerprintRecognitionSystemUsingHybridMatchingTechniques.6thIEEE/ACISInternationalConferenceonComputerandInformationScience(ICIS2007),234-24025.Zhang,W.,Wang,S.,&Wang,Y.(n.d.).Core-BasedStructureMatchingAlgorithm.1026.F.C.J.González,O.O.V.Villegas,V.G.C.SánchezandH.d.J.O.deJesúsOchoaDominguez,"FingerprintRecognitionUsingOpenAlgorithmsinFrequencyandSpatialDomain,"2010IEEEElectronics,RoboticsandAutomotiveMechanicsConference,Morelos,2010,pp.469-474,doi:10.1109/CERMA.2010.11727.LinHong,YifeiWanandA.Jain,(1998).Fingerprintimageenhancement:algorithmandperformanceevaluation,IEEETransactionsonPatternAnalysisandMachineIntelligence,20(8),pp.777-789,doi:10.1109/34.709565SectionsAuthorinformation1.Introduction2.Literaturesurvey3.Dataanalysis4.ConclusionReferencesDOWNLOADFORFREEShareCiteCitethischapterTherearetwowaystocitethischapter:1.ChoosecitationstyleSelectstyleVancouverAPAHarvardIEEEMLAChicagoPlaceholderCopytoclipboard2.ChoosecitationstyleSelectformatBibtexRISDownloadcitationViewBookChaptersPublishwithIntechOpenNextchapterBiometricAuthenticationBasedonElectrocardiogramByM.R.Bogdanov,A.S.Filippova,G.R.ShakhmametovaandNikolaiN.Oskin615downloadsAdvertisementWrittenByMuhammadSarfrazPublished:February10th,2021DOWNLOADFORFREEShareCiteCitethischapterTherearetwowaystocitethischapter:1.ChoosecitationstyleSelectstyleVancouverAPAHarvardIEEEMLAChicagoPlaceholderCopytoclipboard2.ChoosecitationstyleSelectformatBibtexRISDownloadcitation©2021TheAuthor(s).LicenseeIntechOpen.ThischapterisdistributedunderthetermsoftheCreativeCommonsAttribution3.0License,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.ContinuereadingfromthesamebookViewAllIntechOpenBiometricSystemsEditedbyMuhammadSarfrazBiometricSystemsEditedbyMuhammadSarfrazPublished:February10th,2021Chapter2BiometricAuthenticationBasedonElectrocardiogra...ByM.R.Bogdanov,A.S.Filippova,G.R.Shakhmametova...615downloadsChapter3FaceIdentificationUsingLBP-BasedImprovedDirec...ByMohd.AbdulMuqeetandQaziMateenuddinHameeduddi...343downloadsChapter4RegionofInterestLocalizationMethodsforPublic...ByXuLiang,DandanFan,ZhaoqunLiandDavidZhang494downloads