nhan dang van tay su dung mang no ron nhan tao

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i Hc Cng Nghip H Ni KHOA CNG NGH THNG TIN

-------------------

Mn : L Thuyt Nhn Dng

Ti:

Nhn Dng Vn Tay S Dng Mng N Ron Nhn To

Nhm 22 Lp : KHMT2-K3

GV Hng Dn : GV Trn Hng Cng

Danh sch nhm : Nguyn Ngc Tn

Vng Tin Anh

Trnh Quang Ph

Mai Vn Tng

H Ni , Thng 6 - 2011


GII THIEU

1. Gii thieu

2. Tong quan tnh hnh nghien cu

3. Y ngha e tai


CHNG 1:

GII THIEU 1.1 GII THIEU Ngay nay, cac ky thuat sinh trac hoc ngay cang c ng dung rong rai. Trong o, nhan dang van tay c xem la mot trong nhng ky thuat hoan thien va ang tin cay nhat e xac nhan mot ngi. Gan ay, ky thuat nay c chu y nhieu va ngi ta thay rang no thch hp vi nhng ng dung co c s d lieu nho, nhng khong thuan tien cho nhng ng dung co pham vi ln. a so cac he thong bao mat hien nay c bao ve bang password va PIN (Personal Identification Number), nhng cac phng phap nay a c chng minh la khong hieu qua. Bi v, password la nhng con so kho nh, de quen va de b anh cap. Bang cach s dung van tay va mat ma, viec xac nhan mot ngi co the c thc hien bang mot he thong nhan dang van tay an toan va thuan tien. Hnh 1.1 la cau truc c ban cua he thong nhan dang dau van tay. au tien, dau van tay cua mot ngi can c lay mau (bang mot thiet b co the chup c van tay Biometric sensor) va lu vao c s d lieu (Registration module). Sau o, khi can xac nhan ngi o cung cap lai mot dau van tay khac, dau van tay nay se c so sanh vi dau van tay trong c s d lieu e quyet nh chap nhan hay t choi da tren mot gia tr ngng oi sanh.

Hnh 1.1: Cau truc c ban cua he thong nhan dang dau van tay


Hien nay, tren th trng the gii a co ban nhieu loai thiet b chup van tay (fingerprint reader, fingerprint scanner) vi cac chat lng khac nhau. Bang 1.1 gii thieu mot so loai thiet b chup van tay va cac thong so ky thuat cua chung. Hnh 1.2 la anh van tay c chup t cac thiet b nay. Chi tiet hn co the tham khao [15], [16].

Bang 1.1: Mot so loai thiet b chup van tay va cac thong so ky thuat cua chung


Hnh 1.2: Anh van tay c chup t cac thiet b tren: a) Biometrika FX2000, b) Digital Persona UareU2000, c) Identix DFR200,

d) Ethentica TactilSense T-FPM, e) STMicroelectronics TouchChip TCS1AD, f) Veridicom FPS110,

g) Atmel FingerChip AT77C101B, h) Authentec AES4000.


e anh gia mot he thong nhan dang van tay ta can phan tch hai loai loi o la: loi t choi nham (False Reject Rate: FRR) va loi chap nhan nham (False Accept Rate: FAR) Gia tr cua hai loai loi nay co moi quan he vi nhau thong qua gia tr ngng oi sanh T (threshold) la sai lech cho phep gia mau can oi sanh vi mau c lu trong c s d lieu. Khi chon gia tr ngng thap th loi t choi nham se tang, loi chap nhan nham se giam va ngc lai. He thong thng c anh gia theo hai cach:

1. Ty le loi cc tieu SUMmin = (FAR + FRR)min : theo quan iem du la loai loi g th cung la loi, do o ty le loi cc tieu SUMmin la he so loi nho nhat ma he thong co the at c.

2. Mc o loi can bang (Equal Error Rate: EER): o la iem ma FAR va FRR bang nhau.

Hnh 1.3 bieu dien moi quan he gia FAR, FRR, SUM va EER theo ngng T

Hnh 1.3: Moi quan he gia FAR, FRR, SUM va EER theo ngng T

So loi chap nhan nham cua cac van tay khac nhau

Tong so lan oi sanh cua cac van tay khac nhau FAR =

So loi t choi nham cua cac van tay khac nhau

Tong so lan oi sanh cua cac van tay khac nhau FRR =

FAR FRR

EER

SUMmin

SUM = FAR + FRR

T

1

0


1.2 TONG QUAN TNH HNH NGHIEN CU Cac phng phap nhan dang van tay kinh ien eu da vao viec oi sanh (matching) cac iem ac trng (feature) tren van tay. Co nhieu phng phap oi sanh khac nhau. Trong bai nay, chung toi nghien cu phng phap oi sanh bang mang neural nhan tao (Artificial Neural Network). 1.3 Y NGHA E TAI e tai gii thieu mot hng nghien cu va ng dung lnh vc nhan dang van tay vao thc tien. Mot lnh vc a kha pho bien tren the gii nhng con han che Viet Nam.


PHNG PHAP

NHAN DANG VAN TAY

1. Cac iem ac trng tren anh van tay

2. Trch cac iem ac trng

3. Lam noi anh van tay

4. oi sanh (matching)


CHNG 2:

PHNG PHAP NHAN DANG VAN TAY 2.1 CAC IEM AC TRNG TREN ANH VAN TAY

Tren cac anh van tay co cac iem ac trng (la nhng iem ac biet ma v tr cua no khong trung lap tren cac van tay khac nhau) c phan thanh hai loai: singularity va minutiae Singularity: Tren van tay co nhng vung co cau truc khac thng so vi

nhng vung bnh thng khac (thng co cau truc song song), nhng vung nh vay goi la singularity. Co hai loai singularity la core va delta.

Hnh 2.1: Cac iem singularity core va delta

Core thng co mot so dang nh sau:

Hnh 2.2: Mot so loai core thng gap.

core

delta


Minutiae: Khi do theo tng ng van ta se thay co nhng iem ng van ket thuc (Ridge Ending) hoac re nhanh (Bifurcation), nhng iem nay c goi chung la minutiaae.

Hnh 2.3: Cac iem minutiae Ridge Ending (iem ket thuc) va Bifurcation (iem re nhanh)

2.2 TRCH CAC IEM AC TRNG

Bang cac phng phap x ly anh ta co the tm c v tr cac iem ac trng tren cac anh van tay.

2.2.1 Trch cac iem singularity a. Trng nh hng (orientation field)

Anh van tay la anh nh hng, cac ng van la cac ng cong theo cac hng xac nh. Goc hp bi phng cua mot iem tren ng van vi phng ngang c goi la hng cua iem o. Tap hp cac hng cua cac iem tren anh van tay goi la trng nh hng cua anh van tay o.


Hnh 2.4: anh van tay (a) va trng nh hng cua no (b)

Phng phap xac nh trng nh hng nh sau [5], [14]: Chia anh van tay thanh cac khoi nho hn kch thc WxW Tnh gradient theo hai hng x, y la Gx, Gy tai moi iem (pixel) trong khoi Khi o hng cua iem chnh gia cua khoi c xac nh theo cong thc:

( )

=

= =

= =W

i

W

j yx

W

i

W

j yx

jiGjiG

jiGjiG

1 122

1 11

),(),(

),(),(2tan

21

Ham orientation.m thc hien tnh trng nh hng c gii thieu trong phan phu luc.

b. Xac nh cac iem singularity bang ch so Poincare (Poincare index) [3]

Gia s (i,j) la mot iem bat ky tren anh van tay, C la mot ng cong khep knh xung quanh (i,j) th ch so Poincare tai (i,j) la tong ai so cac o sai lech hng cua cac iem lien ke nhau tren ng cong C.

+=i

iN


Hnh 2.7: Cac ket qua cua thuat toan


b. Trch cac iem minutiae trc tiep t anh xam [1] Do theo ng van (Ridge line following) Gia s I la mot anh xam co kch thc la mxn va neu coi chieu th ba z la mc xam tai iem (i,j) th be mat cua anh van tay I co dang nh sau:

Hnh 2.8: Be mat cua anh van tay vi cac ng van (ridge) va cac ranh (ravine)

Theo quan iem toan hoc th ng van la tap hp cac iem cc ai doc theo mot hng xac nh. Viec xac nh cac iem minutiae trc tiep t anh xam da vao thuat toan do theo ng van. Thuat toan nay da vao viec xac nh cac iem cc ai doc theo hng cua ng van. Xac nh iem cc ai Gia s ),),,(( tt ji la thiet dien cua ng van co iem chnh gia la

),( tt ji , hng cua thiet dien 2/ += t ( t la hng cua ng van tai ),( tt ji ) va be rong cua thiet dien m = 2+1 pixel (hnh 2.9). Khi o, c

xac nh nh sau:

va iem cc ai co the c xac nh bang cach so sanh mc xam gia cac iem trong


Hnh 2.9: Thiet dien cua ng van tai

Tom lai viec tm cac iem minutiae bang thuat toan do theo ng van

c thc hien nh sau (chi tiet xem tai lieu tham khao[1]): Lay mot iem bat k (is,js) tren anh I Tm hng s tai iem (is,js) Tm iem cc ai (ic,jc) gan (is,js) nhat

Hnh 2.10: iem cc ai (ic,jc) tng ng vi (is,js)

Tm hng c tai iem (ic,jc) Dch chuyen theo hng c mot oan Tinh chnh lai iem cc ai (ic,jc) va hng c Tiep tuc qua trnh nay e do theo ng van (ridge following) cho en

khi khong phat hien c iem cc ai (ic,jc) th o la iem Ridge Ending hoac cham vao mot ng van khac th o la iem Bifurcation (moi ng van sau khi c do se c gan nhan)

Tiep theo chon mot iem (is,js) khac va thc hien lai qua trnh tren cho en khi do het tat ca cac ng van.


Hnh 2.11: Dch chuyen theo ng van tng oan

Tat ca cac thuat toan tren c thc hien bang ham minutiae.m (phu luc)

2.3 LAM NOI ANH VAN TAY Cac anh van tay thng c lay bang hai phng phap: t mc hoac t cac sensor. Cac anh van tay c lay t mc thng co chat lng thap va khong ong eu. Phan nay se gii thieu phng phap dung bo loc Gabor e cai thien chat lng cua anh van tay [8], [13], [14]. Ham Gabor la mot cong cu hu dung cho viec x ly anh. No co ac tnh chon loc trong mien khong gian lan tan so. Ham Gabor 2_D thc co dang nh sau:

+=

Txyx

Tyxgyx

2cos

21exp),;,( 2

2

2

2

cossin

sincosyxy

yxx+=+=

trong o: la hng cua bo loc T la chu ky cua ham cos (thng c chon t thc nghiem co gia tr [0,1]) x , y la cac o lech chuan (thng c chon t thc nghiem co gia tr [0,4])


Cac bc thc hien: 1. Chuan hoa mc xam: neu I(x,y) la mc xam tai iem (x,y) cua anh I th mc xam chuan hoa Ni(x,y) c xac nh rheo cong thc sau:

trong o:

M0, V0 la mean va variance mong muon (thng c chon la 100) Mi, Vi la mean va variance cua anh I

Chu y: neu mc xam cua cac vung khac nhau tren anh I khong ong eu th co the chia I thanh cac khoi nho va chuan hoa theo tng khoi.

Hnh 2.12: anh I va anh chuan hoa cua no (Ham normalize.m thc hien chuan hoa mc xam c gii thieu phu luc)


2. Xac nh trng nh hng theo phng phap a gii thieu tren 3. S dung ham loc Gabor cho anh a chuan hoa trong mien tan so

Chia anh can loc thanh tng khoi nho kch thc WxW Xac nh hng cua khoi (da vao trng nh hng) Hng cua bo loc la hng cua khoi S dung phep bien oi FFT va phep bien oi IFFT cho tng khoi anh va

ham Gabor

Hnh 2.13: Ket qua loc bang ham gabor_filter.m (phu luc) vi T = 0.6, x = 1, y = 2


2.4 OI SANH (MATCHING) Hau het cac phng phap nhan dang van tay eu da vao viec oi sanh v tr cac iem ac trng. Gan ay, mot so tac gia a ket hp them mot so ac tnh khac cua anh van tay e nang cao hieu qua oi sanh nh: Orientation field [9] hoac Density map [10]. Chi tiet xem tai lieu tham khao, ay toi xin gii thieu phng phap oi sanh v tr cac iem ac trng ma toi a s dung, phng phap nay gan giong vi cac phng phap c neu [4] va [11]. Ham matching.m (phu luc) thc hien oi sanh hai anh van tay theo phng phap nay. Gia s I va I lan lt la cac anh van tay mau va anh van tay can oi sanh,

{ },, yxm = la cac iem ac trng c xac nh bi toa o (x,y) va hng . { } { }

{ } { } njyxmmmmImiyxmmmmI

jjjjn

iiiim

...1,,,,,...,,

...1,,,,,...,,''''''

2'1

'21

======

trong o: m, n lan lt la so iem ac trng cua I va I. Khi o, iem '' Im c coi la giong vi iem Im neu o sai lech ve khong gian va o sai lech ve hng nho hn cac gia tr ngng r0 va 0 :

( )( ) 0''

02'2''

,

)()(,

=+=

ijij

ijijij

mmdd

ryyxxmmsd

Neu th I c coi la giong I. Trong o T la phan tram so iem sai lech cho phep.

Tong so iem cua I so iem giong nhau Tong so iem cua I

< ngng T


MANG NEURAL

NHAN TAO

1. Tong quan ve neural mang neural

2. Mot so mo hnh mang neural


CHNG 3:

MANG NEURAL NHAN TAO

3.1 TNG QUAN V NEURAL MNG NEURAL

1. Bo nao va neuron sinh hoc Te bao than kinh con goi la neuron. Nghien cu sinh hoc ve bo nao con

ngi cho thay rang cac neuron la n v c s am nhiem nhng chc nagn x ly nhat nh trong he than kinh, bao gom: nao, tuy song va cac day than kinh . Moi neuron co phan than va nhan ben trong (goi la soma), mot au than kinh ra (goi la dendrite). Cac day than kinhvao tao thanh mot li day ac xung quanh than te bao, chiem dien tch khoang 0,25mm2, con day than kinh tao rathanh truc dai co the t 1 cm en hang met. ng knh nhan te bao thng ch la 10-4 m. truc day than kinh ra cung co the phan nhanh theo dang cay e noi vi day than kinh vao hoac trc tiep vi nhan te bao cac neuron khac thong qua cac khp noi (goi la synapse). Thong thng, moi neuron co the gom vai chuc cho ti hang tram khp noi e noi vi cac neuron khac. Ngi ta c lng rang li cac day than kinh ra cung vi cac khp noi bao phu dien tch khoang 90% be mat neuron.

Hnh 3.1 Cau tao mang neural sinh hoc Cac tn hieu truyen trong day than kinh vao va day than kinh ra cua cac

neural la tnh hieu ien, c thc hien thong qua cac qua trnh phan ng va giai phong cac chat hu c. Cac chat nay c phat ra t cac khp noi dan ti cac


day than kinh vao se lam tang hay giam ien the cua nhan te bao. Khi ien the nay at en mot mc ngng nao o se tao ra mot xung ien dan ti truc day than kinh ra. Xung nay c truyen theo truc, ti cac nhanh re khi cham ti cac khp noi vi cac neuron khac va se giai phong cac chat truyen ien. Thng chia khp noi thanh 2 loai: khp noi kch thch (excitatory) va khp noi c che (inhibitory).

Phat hien quan trong nhat ve bo nao sinh hoc la cac lien ket khp than kinh kha mem deo, co the bien ong va sa oi theo thi gian tuy thuoc vao cac dang kch thch. Hn na, cac neuron co the san sinh cac lien ket mi vi cac neuron khac; oi khi, li cac neuron co the di tru t vung nay sang vung khac trong bo nao. ay la c s quan trong e giai thch cho c che hoc cua bo nao con ngi.

Cac chc nang c ban cua bo nao bao gom: - Bo nh c to chc theo cac bo thong tin va truy cap theo noi dung. - Bo nao co the tong quat hoa, co the truy xuat cac tri thc hay cac moi lien ket chung cua cac oi tng tng ng vi mot khai niem chung nao o. - Bo nao co kha nang ieu chnh hoac tiep tuc thc hien ngay khi co nhng sai do thong tin b thieu hay thieu chnh xac. Ngoai ra, bo nao con co the phat hien va phuc hoi cac thong tin b mat da tren s tng t gia cac oi tng. - Bo nao co kha nang xuong cap va thay the dan. Khi co nhng truc trac tai cac vung nao (do chan thng) hoac bat gap nhng thong tin hoan toan mi la, bo nao van co the c tiep tuc lam viec. - Bo nao co kha nang hoc. Nhn chung, tnh toan s bo cho thay rang du bo vi x ly may tnh ien t

co the tnh toan nhanh hn hang trieu lan so vi neuron cua bo nao, nhng xet tong the th bo nao lai tnh toan nhanh hn hang ty lan. Ngoai ra, cung de thay rang bo nao con ngi co the lu tr nhieu thong tin hn cac may tnh hien ai, du rang ieu nay khong phai ung mai mai bi le bo nao tien hoa cham con bo nh may tnh th c nang cap rat nhanh nh nhng tien bo cua khoa hoc ky thuat.

2. Mo hnh neuron nhan tao va mang neuron nhan tao mang neuron nhan tao (Artificial neural network ANN) la mang bao gom

cac nut (neuron, n v x ly) c noi vi nhau bi cac lien ket neuron. Moi lien ket kem theo mot trong so nao o, ac trng cho ac tnh kch hoat hoac c che gia cac neuron. Co the xem cac trong so la phng tien e lu thong tin dai han trong mang neuron, con nhiem vu cua qua trnh huan luyen (hoc) la cap nhat cac trong so khi co them thong tin ve cac mau hoc, hay noi cach khac, cac


trong so c ieu chnh sao cho dang ieu vao ra cua no mo phong hoan toan phu hp moi trng ang xem xet.

a. Mo hnh nhan tao

Hnh 3.2 Mo hnh neural nhan tao Moi nueron c noi vi cac neuron khac va nhan c cac tn hieu t

chung vi cac trong so wj. - Tong thong tin vao co trong so la: - Net = jj sw , ay la thanh phan tuyen tnh cua neuron - Ham kch hoat g ong vai tro bien oi t Net sang tn hieu au ra out - Out = g(Net), ay la thanh phan phi tuyen cua mang neuron - Mot so dang ham kch hot thng dung trong thc te:

+ Hm bc: step(x)=

nhan dang van tay su dung mang no ron nhan tao

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