FINGERPRINT

FINGERPRINT RECOGNITIONUNDER THE GUIDENCE OF NIRAJ KUMAR KUSHWAH Dr.D.K.SRIVASTAVA ROLL NO. 1104331033

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CONTENTFINGERPRINTPATTERNFINGERPRINT RECOGNITIONLEVEL OF DESIGNOPTICAL FTIR SENSORMINUTIA EXTRACORMINUTIA MATCHERAPPLICATIONADVANTAGES & DISADVANTAGESCHARACERSTIC

FINGERPRINT RECOGNITION2FINGERPRINT Human fingertips are consists of ridges and valley and they mixing together form dinstictive pattern. Those pattern are called fingerprint.FINGERPRINT RECOGNITION3

FINGERPRINT patternArch (5%)Whorl (30%)Loop (65%)FINGERPRINT RECOGNITION4

ArchWhorlLoop minutia

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VERIFICATIONFingerprint verification is the method where we comparea claimant fingerprint with an enrolee fingerprint, where our aim is to match both the fingerprints.

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FINGERPRINT RECOGNITION7IDENTIFICATIONFingerprint identification is mainly used to specify any persons identity by his fingerprint. Identification has been used for criminal fingerprint matching.

SYSTEM LEVEL DESIGNFingerprint recognition system contains :sensorminutia extractorminutia matcher

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SENSOROPTICAL FTIR SENSOR

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MINUTIA EXTRACTORTo extract a minutia a three step approach is used such as FINGERPRINT RECOGNITION10

IMAGE ENHANCEMENT Fingerprint image enhancement is used to makeimage clear for better use which is very easy tohandle and can operate easily for furtheroperation.

FINGERPRINT RECOGNITION11Image after enhancement

Original Image IMAGE BINARIZATIONwe basically binarize the image by extracting thelightness of the image that is here we extract thebrightness and density of the image.

FINGERPRINT RECOGNITION12Enhanced Image Image after Binarization

IMAGE SEGMENTATIONwe basically partitioning a digital imagein to multiple segments that is a set ofpixels,It also well known as super pixels.

The image area without effective ridgesand furrows holds background information.So the effective ridges and furrows deletedfirst.

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THINNINGThe ridge thinning process is used to eliminatethe redundant pixels of ridges till the ridges arejust up to one pixel wide. bwmorph(binaryImage,thin,Inf) bwmorph(binaryImage, hbreak, k) bwmorph(binaryImage, clean', k) bwmorph(binaryImage, spur', k)

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MINUTIA MARKINGminutia marking is done by using 3 x3 pixel window as follows. In this case the concept of Crossing Number (CN) is mainly used. FINGERPRINT RECOGNITION15

BIFURCATION TERMINATION REMOVE FALSE MINUTIAFalse minutia such as false ridge break are generated due to insufficient amount of ink and the cross connection between the ridges occurs.

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MINUTIA MATCHERsame fingerprint implies same number of minutiae. Minutia are matched together by their distance relative to other minutia around it

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APPLICATIONDrivers licence.Terrorist identiification.Medical recordsCriminal investigationLogging into a computer

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ADVANTAGES & DISADVANTAGESAdvantagesNo need of password to remrmber.Fastere login.Cheapest Disadvantagescant access the system in case of burn the finger.

FINGERPRINT RECOGNITION1919CHARACTERSTICSMale FemaleFemale subjects have worse image qualityRight Hand Left HandLeft hand fingerprint quality is worse than right handBy Age of SubjectImage Quality worsens as subject age increasesFINGERPRINT RECOGNITION20REFERENCES1.D. Maltoni, D. Maio, and A. Jain, S. Prabhakar, 4.3: Minutiae-based Methods (extract) from Handbook of Fingerprint Recognition, Springer, New York, pp. 141-144, 2003. 2. D. Maio, and D. Maltoni, Direct gray-scale minutiae detection in fingerprints, IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 19(1), pp. 27-40, 1997. 3. L. Hong, "Automatic Personal Identification Using Fingerprints", Ph.D. Thesis, 1998 4. K. Nallaperumall, A. L. Fred and S. Padmapriya, A Novel for Fingerprint Feature Extraction Using Fixed Size Templates, IEEE 2005 Conference, pp. 371-374, 2005 5. Wikipedia link - http://en.wikipedia.org/wiki/Fingerprint_recognition 6. Fingerprint Recognition, Paper by WUZHILI (Department of Computer Science & Engineering, Hong Kong Baptist University) 2002 .

FINGERPRINT RECOGNITION2121 THANK YOUFINGERPRINT RECOGNITION22