Anall Univrsităţii d Vst din Timişoara Vol. LII, 2008 Sria Fizică PHASE-OLY CORRELATIO I FIGERPRIT DATABASE REGISTRATIO AD ATCHIG Alin C. Tusda, 2 Gianina Gabor Univrsity of Orada, Environmntal Faculty, Gn. aghru 26, 40088 Orada, Romania 2 Elctrical Enginring & Information Tchnology Faculty, Univrsitatii Strt, 40087 Orada, Romania Abstract. Do This papr prsnts fingrprint rgistration and matching in a fingrprint databas using phas-only corrlation tchniqus. Two modifid phas-only corrlation tchniqus with fficint rgistration rsults ar usd: th rctangl band limitd phas-only corrlation mthod (BPOC) and an lliptic limitd phas-only corrlation mthod (EPOC) th last on bing proposd by th authors. Th rsults of th computr simulations obtaind for ths two mthods ar analyzd on th sam fingrprint databas and th analysis dnots that th proposd mthod EPOC has bttr prformancs than BPOC mthod for fingrprint matching in th usd databas. Kywords: pattrn rcognition, optical corrlators, imaging dtctors and snsors.. Introduction Scurity systms ar usd on larg scals in ordr to provid or not accss to rsourcs. For vry scurity systm rstriction ruls can b built and implmntd basd on svral critria. Biomtrics is a popular scurity critrion and is usd to rstrict accss to systms and prsrv thir scurity. Th most widly usd biomtric is fingrprint rcognition or matching. Th fingrprint rcognition mthod has bn usd as an ffctiv prsonal idntification mthod sinc it has rlativly high rliability, stability and procss spd compard with othr rcognition mthods. Du to a highr dmand nowadays on fingrprint rcognition srvics rsarch mthods usd to acquir fingrprints through lctronic mdia and automat fingrprint rcognition basd on th digital rprsntation of fingrprints wr dvlopd. On of th most popular fingrprint rcognition mthod considrd from th svral mthods dvlopd in th past yars for fingrprint rcognition is th phas-only corrlation (POC) on [-6]. This fingrprint rcognition mthod is important bcaus its sub-pixl imag translation capability. Past xprimnts dvlopd a modifid phas-only corrlation (POC) 93
mthod namd (BPOC) implmntd by rctangular band filtring th cross-spctrum of th POC function in ordr to improv th gnuin-impostor rjction [4, 6]. Th papr stars with a brif thortical prsntation of phas-only corrlation (POC) tchniqu and two modifid phas-only corrlation tchniqus BPOC and EPOC. Follow som xprimntal rsults and analysis that compar ths two modifid phas-only corrlation tchniqus with fficint rgistration rsults: a rctangl band limitd phas-only corrlation (BPOC) mthod and an lliptic limitd phas-only corrlation (EPOC) mthod, th last on bing proposd by th authors. Th rsults of th xprimnts dnot that th proposd mthod EPOC has bttr prformancs (highr GAR valus gnuin accptanc rat and lowr FRR valus fals accptanc rat) than BPOC mthod for fingrprint matching for th usd databas. 2. Fingrprint rcognition mthods atching procss is usd for objct rgistration that mans that on objct is compard with svral objcts. Comparison critria concluds if th compard objcts or not similar with othr objcts. Th comparison procss works basically with two objcts. In our cas th comparison mthod is th cross-corrlation and th objcts ar th fingrprints. In a singl cross-corrlation procss th two objcts ar dnotd as rfrnc and non-rfrnc. That mans from cross-corrlation procss w obtain th information of th rfrnc is similar or not with th non-rfrnc objct. Th classical cross-corrlation considrs two ( ) imags, rf ( x, as rfrnc imag and nrf ( x, as non-rfrnc imag. Th 2D discrt Fourir transforms of ths imags, dnotd as Rf ( and Rf (, ar givn by Rf ( iϕ rf ( i = REF(, Rf ( REF( ϕ nrf ( = g) = [ Rf ( Rf ( )] 0. 5, REF( [ Rf ( Rf ( ] 0. 5 REF( v = h) whr REF ( and REF ( ar th amplitud part, ϕ ( and ϕ (, ar th phas part of th 2D discrt Fourir transforms. Classical corrlation function, ClC R (, is th 2D invrs discrt Fourir transform of classical cross-spctrum, givn by rf nrf 94
ClC( x, = u = v= REF( REF( i ϕ ( rn ux vy i) This 2D function prsnts a highly wid cross-corrlation pak whn rf ( x, = nrf ( x,. Whn rf ( x, nrf ( x, thn th cross-corrlation pak strongly dcrass. Phas-only Cross Corrlation Th phas-only cross-spctrum [, 4-6] is dfind by PO _ CS( i i ϕrn ( REF( REF( i ϕrn ( = = ϕ u v i) rn (, ) REF( REF( and thus th phas-only cross-corrlation is givn by 2D Fourir transform of th phas-only cross-spctrum POC( x, = u = v= i ϕ rn ( ux vy ii) If rf ( x, = nrf ( x, thn ϕ ( 0 and th phas only corrlation is giv by rn POC( x, = u = v= ux vy = δ ( x, iii) this mans that if th two imags ar idntical thn th POC givs a highly sharp pak so th matching accuracy is highr than in th classical mthod. Band Limitd Phas-only Cross-corrlation Th cross-corrlation procss on a databas is basically charactrizd by two quantitis: th autocorrlation pak intnsity (API) and th cross-corrlation pak intnsity (CPI). Th API valu is obtaind from all autocorrlations btwn th nw fingrprint and th gnuin class fingrprints as witnss fingrprints. or prcisly th minimum valu from this st of autocorrlations paks is dnotd as API. In th sam mannr th CPI valu is th 95
maximum valu of all th othr cross-corrlation paks gnratd with th impostor classs fingrprints. Phas-only corrlation is a vry prcis matching mthod and is ffctiv for th vrification procss. This is don by fin comparing of th high frquncis in th Fourir transforms of th fingrprints. Whn on has to rgistr a nw fingrprint thn th corrlation procss must match it with som dformd rprsntations of it. Th dformations altr xactly th high frquncis. Th rfrnc-witnss corrlation can hav a lowr API valu than th rfrnc-nonrfrnc corrlation CPI valu. This mans that th involvd matching procss fails (Fig. a, b, c & Fig. 2 a, b). Fingrprint databas rgistration matching procss has to corrlat only frquncis that ar common to all fingrprints from th sam class. This is th rason why th band limitd phas only corrlation (BPOC) was introducd [4, 6]. This corrlation uss a 2D band filtr on th phas-only cross-corrlation spctrum. Th band filtr is dfind with two sub-unitary valud cofficints: ovr th rows dirction, cl, and ovr th columns dirction, cc. a b c FIGURE. Fingrprint xampls: a rfrnc; b witnss (gnuin class); c non-rfrnc (impostor class). a b FIGURE 2. Phas-only corrlation rsults btwn: a rfrnc and witnss (sam gnuin class); b rfrnc and non-rfrnc class (diffrnt classs). 96
a b FIGURE 3. Band limitd phas-only corrlation rsults btwn: a rfrnc and witnss (sam gnuin class); b rfrnc and non-rfrnc class (diffrnt classs). Th BPOC rsults from Fig. 3a and Fig. 3b, show that th matching procss is succssful as th API valu (Fig. 3a) is gratr than th CPI valu (Fig. 3b). 3. Elliptic band limitd phas-only cross-corrlation Th authors propos a nw fingrprint rcognition mthod, th lliptic band phas-only corrlation mthod (EPOC). Th nw mthod uss an lliptic band filtr with th sam cl and cc paramtrs instad of a rctangl band filtr with cl and cc paramtrs. Th rason of using an lliptic band filtr this is that th powr spctrum of th fingrprints usually prsnts th highst dnsity of th information in a cntrd lliptic form. As mntiond bfor, this cntrd llips contains that kind of spatial frquncis that can accommodat th databas fingrprint rgistration. a CorrRW b CorrR FIGURE 4. Elliptic band limitd phas-only corrlation rsults btwn: a rfrnc and witnss (sam gnuin class); b rfrnc and non-rfrnc class (diffrnt classs). Th BPOC rsults from Fig. 4a and Fig. 4b, show that th matching procss is succssful as th API valu (Fig. 4a) is gratr than th CPI valu (Fig. 4b). 97
4. Exprimnts and rsults In this papr, a fingrprint databas was usd which was scannd with Cross atch Vrifir 300 Classic (USB) at 500dpi in 30.5 30.5 mm imag siz (http://www.nurotchnologija.com/download/crossatch_sampl_db.zip). Th databas contains fingrprint classs with 6 fingrtips 8 diffrnt scannd fingrprints for ach of th 76 prsons. Th fingrprint indx dnots ppp_ff_s.bmp, as ppp is th prson numbr, ff is th fingrtip numbr and s is th numbr of th fingrprint vrsion. Th xprimntal rsults from th BPOC and EPOC ar prsntd in Fig.5, for th prson with indx 2 and fingrtip indx 3, 4, 5, 6, 7, 8, ovr th sam st of fingrtips of prsons with indxs 3, 4, 7, 22, 27, 45, 47, 76. Th band limitd POC paramtrs wr slctd with th valus: cl=0.80 and cc=0.45. Thr ar prsntd th Gnuin Accptanc Rat, GAR, and th Fals Rjction Rat, FRR. Th GAR is calculatd whn th Fals Accptanc Rat is FRR=0. This mans that thr was slctd a thrshold valu (Th C ), which is th highst valu from all th maximum intnsity of th cross-corrlation paks (CPI). Gnuin class POC valus highr than Th C wr considrd in GAR calculation whil th smallr ons wr considrd in FRR calculation. 00 90 80 70 60 50 40 30 20 0 0 GAR (FAR=0) BPOC cl=0.8, cc=0.45 GAR (FAR=0) EPOC cl=0.8, cc=0.45 FRR (FAR=0) BPOC cl=0.8, cc=0.45 FRR (FAR=0) EPOC cl=0.8, cc=0.45 2_3 2_4 2_5 2_6 2_7 2_8 FIGURE 5. Fingrprint phas-only corrlation comparativ rsults obtaind for th prson with indx 2 for BPOC and EPOC mthods. Th EPOC tchniqu has th highst GAR valu for all six fingrtips of th prson with indx 2, in an xprimnt with 336 (7 prsons 6 fingrtips 8 scans) 48(prson with indx 2 6 fingrtips 8 scans) = 6,28 POC corrlations. 98
In this xprimnt th diffrncs of GAR cofficints prformd with EPOC and BPOC tchniqus for th sam fingrtip lis btwn 3.44% and 5.38%. From th tchnological point of viw only th 3.44% diffrnc gain is intrsting bcaus this is th ovrall dtction fficincy that accommodats th usd fingrprint databas. 5. Conclusions Th papr prsnts two modifid phas-only corrlation mthods - th rctangl band limitd (BPOC) and th proposd lliptic band limitd (EPOC). Ths matching mthods ar vry fficint for fingrprint rcognition whn using singl corrlation xprimnt. Th rsults obtaind using simulation mphasiz that lliptic band limitd phas-only corrlation (EPOC) mthod proposd by th authors has bttr prformancs (highr GAR valus) than th rctangl band limitd phas-only corrlation (BPOC) mthod. Thus, for fingrprint databas rgistration th lliptic limitd phas-only corrlation (EPOC) mthod is mor fficint than th rctangl band limitd phas-only corrlation (BPOC) mthod. Our futur rsarch will dvlop a mor robust lliptic limitd phas-only corrlation (EPOC) mthod to gomtrical dformations of th fingrprints with a Log-Polar transform. In th nar futur w also intnd to work with a largr/much largr fingrprint databas to nsur statistical significanc. W also and intnd to hav th possibility to us this databas in biomtrics. Rfrncs. L. H. Chin and T. Aoki, "Robust motion stimation for vido squncs basd on phasonly corrlation", Procdings of th 6th IASTED Intrnational Confrnc on Signal and Imag Procssing, August 2004, pp. 44 446. 2.. Uchida, T. Shibahara, T. Aoki, H. akajima, and K. Kobayashi, 3D fac rcognition using passiv stro vision", Procdings of IEEE Intrnational Confrnc on Imag Procssing, Sptmbr 2005, pp. II-950--II-953. 3. K. iyazawa, K. Ito, T. Aoki, K. Kobayashi, and H. akajima, An fficint iris rcognition algorithm using phas-basd imag matching, Procdings of IEEE Intrnational Confrnc on Imag Procssing, Sptmbr 2005, pp. II-49--II-52. 4. K. Ito, A. orita, T. Aoki, T. Higuchi, H. akajima, and K. Kobayashi, A fingrprint rcognition algorithm using phas-basd imag matching for low-quality Fingrprints, Procdings of IEEE Intrnational Confrnc on Imag Procssing, Sptmbr 2005, pp. II-33--II-36 99
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