NIST Fingerprint Image Quality. Elham Tabassi Biometric Consortium Conference September 20, 2005

Transcription

1 NIST Fingerprint Image Quality Elham Tabassi Bimetric Cnsrtium Cnference September 20, 2005

2 backgrund quality is imprtant previus research mstly defined as a measure f the extractability f the features used fr recgnitin such as minutiae. lcal rientatin infrmatin (Blle et al, Shen et al, Hng et al., ) glbal features (Hng et al, Lim & Ya, Nill & Buzas, ) almst all used subjective quality assessment t evaluate their quality algrithm size f fingerprint, pressure, humidity, amunt f dirt, elham.tabassi@nist.gv

3 quality as predictin f perfrmance we define fingerprint image quality as a predictin f a matcher perfrmance, e.g. a sample s quality scre reflects the predictive psitive r negative cntributin f an individual sample t the verall perfrmance f a fingerprint matching system. TAR excellent quality samples result in high perfrmance pr quality samples result in lw perfrmance FAR elham.tabassi@nist.gv

4 use f quality t imprve perfrmance recapture samples f insufficient quality pruning the prest quality samples (1.65% f dataset) reduced EER frm.0047 t (sdki - ds - ri) prcess samples differently based n their qualities cllect relevant statistics cmpare capture devices and/r envirnments crrelatin amng fingers p(nfiq(ri)=5) = p(nfiq(li)=5) = p(nfiq(li)=5 nfiq(ri)=5) = 0.22 cause higher quality sample dminate fusin elham.tabassi@nist.gv

5 NIST Fingerprint Image Quality NFIQ quality number =1 =5 NFIQ s 5 levels f quality are intended t be predictive f the relative perfrmance f a minutia based fingerprint matching system. NFIQ=1 indicates high quality samples, s lwer FMR and/r FNMR is expected. NFIQ=5 indicates pr quality samples, s higher FMR and/r FNMR is expected. elham.tabassi@nist.gv

6 perfrmance target degree f separatin between a sample s s genuine and impster distributins sd29 - vtb match and nn match scres histgram 0.15 match scres nn match scres 0.10 pr nmatch match excellent quality f a bimetric sample x i predictin f the bin its nrmalized match scre falls elham.tabassi@nist.gv

7 pair-wise quality Q 1 Q 2 pairwise quality similarity H(Q 1,Q 2 ) Qscre 12 fingerprint matching algrithm when the enrllment sample is f gd quality and better than that f the use phase (search) sample, the search sample s quality is sufficient t predict perfrmance. elham.tabassi@nist.gv

8 NIST Fingerprint Image Quality feature extractin NFIQ neural netwrk quality number feature extractin: cmputes apprpriate signal r image fidelity characteristics and results in an 11-dimensinal feature vectr. neural netwrk:classifies feature vectrs int five classes f quality based n varius quantiles f the nrmalized match scre distributin. quality number: an integer value between 1(highest) and 5 (prest). elham.tabassi@nist.gv

9 NFIQ effectiveness evaluatin criterin is rank ROC as a functin f image quality used varius fingerprint matching algrithms and varius datasets t evaluate NFIQ 15 different COTS fingerprint matching algrithms 22 different datasets f different fingers captured by varius devices and at different peratinal settings each test dataset has 2 fingerprint images f 6000 persn cmpared (TAR,FAR) f levels f quality at a fixed threshld as quality degrades, true accept rate decreases fr all the matchers, FAR increase fr sme. levels 2,3,4, and 5 are statistically separable. It takes abut ne third f a secnd t cmpute quality f a flat fingerprint image. elham.tabassi@nist.gv

10 6000 subjects - Right index (far,tar)=(0.012,0.99) quality excellent verygd gd fair pr FAR TAR

11 separable levels f quality Fr each quality level, we calculated 95% cnfidence intervals f FAR=0.1% fr six matchers and sixteen datasets. nfiq levels 2,3,4, and 5 are statistically separate. elham.tabassi@nist.gv

12 cnclusin a nvel definitin f fingerprint image quality NFIQ wrks as a rank statistic fr perfrmance fr all 330 cmbinatins f COTS fingerprint matchers and peratinal datasets tested NFIQ levels 2,3,4, and 5 are statistically independent NFIQ can be used fr real-time quality assessment NFIQ is publicly available but subject t US exprt cntrl laws (fingerprint.nist.gv) elham.tabassi@nist.gv

13 thanks