3D Fingerprint Matching using Optical Coherence ...

3D Fingerprint Matching using Optical Coherence Tomography (OCT) I M A G O R E S E A R C H G R O U P - U N I V E R S I D A D E F E D E R A L D O PA R A N Á – B R A Z I L W W W. I M A G O . U F P R . B R

Schedule 1.  2D Fingerprints 2.  Previous Research – Newborn Fingeprint Iden=fica=on 3.  3D Fingerprint Analysis – Mo=va=on 4.  3D Fingerprint Matching – Challenges 5.  Op=cal Coherence Tomography 6.  Skin layers – Proposed approach - Matching of 2D-3D Fingerprints 7.  Tests and Results 8.  Conclusions

Fingerprints  Mature biometrics, largely adopted  Large databases available (IAFIS – more than 70 million people)  Sensor technologies: op=cal, capaci=ve, thermal, ultrasound  Feature level classifica=on: ! Level 1: ridge flow and general paXerns ! Level 2: minu=ae ! Level 3: pores, edge texture ! Matching: Minu=ae ! Strategies: triplets, similar graphs, type/orienta=on

Previous Research Works Newborn Babies Identification

Newborn Identification – A global challenge

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Newborn Babies identification – Social Problem !  Baby Swaps: 1 baby swap in 6,000 births in Brazil !  Children disappearance es=mated by UNICEF (1.2 Million children annually worldwide), 40,000 in Brazil (10% of children never found) !  In USA, 500,000 children reported missing every year !  Kidnaps, illegal adop=on and children traffic !  First 24 hours aber a child is reported missing are cri=cal

Newborn Babies Identification – Social Problem ! Baby footprint stamps are ineffec=ve for iden=fica=on ! Usually obtained with ink and paper ! Poor image quality ! Affected by moisture and dirt ! Acquired by untrained people

Challenges - Acquisition !  Skin ridges and valleys 2 to 3x smaller than in adults !  Need 1,500 dpi to capture ridges/valleys with precision !  Skin easily deformable !  Moisture and dirt (vernix caseosa) !  Scanning issues: " Parents anxiety " Mo=on during acquisi=on " Too much pressure against sensor " No formal procedure

Our Research ! Use of Palmprint for newborn iden=fica=on ! Custom digital scanner (high resolu=on) device to newborns ! Formal acquisi=on procedure (protocol) ! Newborn baby palmprint database ! 1,221 images from 250 babies – 1,000 dpi ! Quality criteria to classify newborn palmprint

3D Fingerprint matching

Motivation ! BeXer matching accuracy is in crescent demand (border protec=on, iden=fica=on of terrorists) ! Fraud: fake fingerprints, fingerprint altera=on, ! Approximately 5% of people cannot have fingerprint scanned (diseases, cancer treatment, labor-related issues) ! Iden=fica=on of people aber catastrophes (finger skin damaged)

Ref. [4]

3D Fingerprint – characteristics !  3D fingerprints make available a rich amount of informa=on that can be used for biometric iden=fica=on improvement ! Minu=ae spa=al posi=on ! Finger curvatures ! Ridges and valleys curvatures ! Unrolled fingerprints

Challenges (newborns, frauds) requirements Difficul,es

Poten,al solu,on

Skin deformability

Touch-less scanning

Small dimensions ( ridges and valleys)

High resolu=on > 1500 dpi , < 1μm

Moisture and dirt

Touch-less, immunity to moisture and dirt

Not possible to scan/altera=ons

Use of internal layer (dermis) for iden=fica=on

Accuracy improvement

Use of other dis=nc=ve skin informa=on

Biomedical imaging modalities

Optical Coherence Tomography  Harmless technology: uses low power light (near infrared) # Touch-less (no deforma=on, more comfortable) # Direct 3D acquisi=on in high resolu=on (