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1、IEEETRANSACTIONSONPATTERNANALYSISANDMACHINEINTELLIGENCE,VOL.20,NO.8,AUGUST1998777FingerprintImageEnhancement:AlgorithmandPerformanceEvaluationLinHong,StudentMember,IEEE,YifeiWan,andAnilJain,Fellow,IEEEAbstract—Acriticalstepinautomaticfingerprintmatchingistoautomat
2、icallyandreliablyextractminutiaefromtheinputfingerprintimages.However,theperformanceofaminutiaeextractionalgorithmreliesheavilyonthequalityoftheinputfingerprintimages.Inordertoensurethattheperformanceofanautomaticfingerprintidentification/verificationsystemwillber
3、obustwithrespecttothequalityofinputfingerprintimages,itisessentialtoincorporateafingerprintenhancementalgorithmintheminutiaeextractionmodule.Wepresentafastfingerprintenhancementalgorithm,whichcanadaptivelyimprovetheclarityofridgeandvalleystructuresofinputfingerpri
4、ntimagesbasedontheestimatedlocalridgeorientationandfrequency.Wehaveevaluatedtheperformanceoftheimageenhancementalgorithmusingthegoodnessindexoftheextractedminutiaeandtheaccuracyofanonlinefingerprintverificationsystem.Experimentalresultsshowthatincorporatingtheenha
5、ncementalgorithmimprovesboththegoodnessindexandtheverificationaccuracy.IndexTerms—Biometrics,fingerprint,minutiae,enhancement,Gaborfilters,performanceevaluation.——————————F——————————1INTRODUCTIONINGERPRINTidentificationisoneofthemostimpor-Ftantbiometrictechn
6、ologieswhichhasdrawnasub-stantialamountofattentionrecently[12],[15].Afinger-printisthepatternofridgesandvalleys(alsocalledfur-rowsinthefingerprintliterature[14])onthesurfaceofafingertip.Eachindividualhasuniquefingerprints.Theuniquenessofafingerprintisexclusivelyde
7、terminedbythelocalridgecharacteristicsandtheirrelationships[12],[14].Atotalof150differentlocalridgecharacteristics(islands,shortridges,enclosure,etc.)havebeenidenti-fied[14].Theselocalridgecharacteristicsarenotevenlydistributed.Mostofthemdependheavilyontheimpres-s
8、ionconditionsandqualityoffingerprintsandarerarelyobservedinfingerprints.Thetwomostprominentlocalridgecharacteristics,calledminutiae,are(a)1)ridgeending
