GIAI THUAT PHAN DOAN ANH CHI BAN VAN TAY MU'C

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Tap chi Tin hgc va Dieu khien hgc, T.26, S.2 (2010), 253-266

GIAI T H U A T PHAN DOAN ANH CHI BAN VAN TAY MU'C;! NGON

NGUYEN THI HUONG THUYi, NGUYEN NGOC MINH^, NGUYEN NGOC KY^

' ^ Tong cue IV, Bg Cong an 2 Trung tdm CNTT - EVN

A b s t r a c t . This paper proposes a novel algorithm for segmenting fingerprints from ten-print card images. The proposed algorithm is constituted of two stages. The coarse stage uses the normalization, the smoothing, the binary transformation and then the contour following technique to cutting out a ten-print card image into twenty small fingerprints. Then, the fine stage uses the mean, the variance, the length and the directional features of the ridge segments obtained after vectorisation and piecewise linear approximation to more detail detecting the good quality fingerprint region from the noisy regions. The experimental results providing on FVC2004 DB2 and C@FRIS DB showed that the proposed algorithm worked more efficiently and gained the better precision in comparison with other methods using raster approach.

T o m t a t . Bai bao de xuat mot giii thuat mdi de phan doan van tay tir inh bieu mau chi bdn mudi ngdn. Giii thuat de xuat bao gom hai cdng doan. Cdng doan thd xii ly cat tach inh bieu mau chi bin mudi ngdn thanh hai muai inh ngdn rieng re dua tren ky thuat tfen xu ly inh nhu chuan hda, lam tran, chuyen dd'i nhi phan va sau dd tien hanh do bien. Cdng doan min khai thac cac thudc ti'nh truyen thdng nhu gia tri trung binh, phuang sai muc xam va bo sung them cac thuoc ti'nh mdi theo hudng tiep can vector. Cac thudc tfnh mdi nhu do dai, do cong va nang lugng thay doi hudng ciia cac doan da tuyen xap xi dudng bien thu dugc sau khi vecta hoa va xap xi tuyen tinh tirng doan de xii ly tach vimg van chat lugng cao khdi vimg nen va vimg nhieu tren inh van tay tirng ngdn. Ket qui thuc nghiem dugc tien hanh tren CSDL FVC2004 DB2 va CSDL CFRIS DB thuc te ung dung da chirng td giii thuat de xuat hoat ddng hieu qui, dat do chfnh xac cao han cac phuang phap chi dimg cac thudc tfnh theo hudng tiep can raster.

1. M d T D A U

Trong n h i n dang v i n tay, van de phan doan (segmentation) dugc hieu la cdng doan xu ly tach viing van tay can quan t i m ra khoi phan nen ciia inh. Do su da dang ciia cic loai p h u a n g tien thu n h i n v i n tay cung nhu cic loai hinh ung dung, chii de nay van dang thu hilt sir quan tam ciia nhieu nhdm nghien ciru [1, 5, 8,14,15,17,21,24]. Vdi miic dp cao han, lien quan den d i n h gii chat lugng v i n tay, phan doan v i n tay theo nghia tim vimg quan t i m chat lugng cao va coi dd nhu "mien van tay x i c dinh" la mdt chii de dang dugc t i p trung nghien ciru. Tren ca sd viing chat lugng v i n tay dugc xac dinh, ngudi ta cd the tien hanh danh gia do tin cay ciia cic diem d i e trung dua tren thuc te l i tren viing v i n tay rd cic diem dac trung trich chpn dugc thudng cd do tin cay cao ban so vdi tren viing van tay nhieu

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254 NGUYEN THI HUONG THUY, NGUYEN NGOC MINH, NGUYEN NGOC KY

va tren vimg nen. Viec gidi ban lai "mien xic dinh" ciia rridi van tay cdn la thdng tin quan trgng giiip cho qua trinh ddi sinh hieu q u i han nhd xic dinh dugc mien "giao chung" ciia hai van tay va gian luge bdt cic phep so sanh khdng can thiet ddi vdi cac die diem chi tiet nam ngoai vimg giao chung niy.

Vdi tam quan trgng ndi tren, cd nhieu cdng trinh nghien cuu vdi nhieu giii thuat phin doan de tich viing van chat lugng cao dugc de xuat [4, 6, 7,11, 25]. Cac giii thuat phan doan nhin chung deu tap trung giii quyet bii toin nhan dang hai ldp, ldp nen va ldp viing vin quan tam, theo hudng khai thic cic thudc tfnh d muc pixel theo hudng tiep can raster nhu gii tri trung binh, phuang sai miic xim v i dp hgp hudng (coherence), sau dd dung cic bp phan loai tuyen tfnh hai ldp de tich viing. Tuy nhien, cac danh gii dua ra deu chii yeu dimg cic ket qui phan tfch cic diem inh va vimg ciia so lan can dua theo hudng tiep can raster.

Nhugc diem ciia hudng tiep can nay la do phiic tap tfnh toan Idn do phii truy cap va phin tfch tat ci cac diem inh trong tirng cua so anh (block), nhay cim vdi sir da dang ciia nhieu cue bd va phan Idn mdi chi tien hanh tren cac mau van tay dan 1^, thu nhin tir thiet bi thu nhin van tay sdng cd phan nen cd nhieu diem khic vdi phan nen tren chi bin giay nen khi dua vao cii dat de phan doan chi bin giay ciia nude ta thi xuat hien nhieu ldi, die biet la ddi vdi cac chi bin cd nen giay chat lugng xau (mau xanh, man tfm, mau ghi sam). De cd giii phip phii hgp, nham dua vio ling dung de tu ddng hoa cac tang thu chi bin nen bang giay ciia thuc te nude ta vdi nhieu loai nen man da dang va phuc tap, bai bio niy t i p trung nghien cuu va de xuat giii thuat phin doan cic mau chi bin chii yeu dugc in tren giay, tieu bieu nhat la mau chi bin 10 ngdn (Theo mau A7 va tua A7) dang dugc diing pho bien hien nay d nude ta. Thuc ra cic loai bieu man thu nhin vin tay 10 ngdn hien dung d nude ta deu dua tren miu gdc ciia Cue dieu tra lien bang FBI (My) nhung qua hang chuc nim sir dung da bi cii bien ndi dung v i thay doi man in nhieu lan lam hinh thanh nen mdt lap chi bin 10 ngdn tam gpi la lech chuan. Giii thuat phan doan chi bin 10 ngdn de xuat dugc tien hanh theo hai cdng doan. Cdng doan phin doan cat inh thd sir dung ket hgp cac ky thuat tien xir ly nhu chuan hda, lam tran inh chi bin, chuyen doi nhi phan va sau dd tien hanh dd bien de xir ly tich inh chi bin dau vio thanh hai muai inh ngdn rieng re. Cdng doan phin doan min chgn hudng tiep can mdi, khdng xir ly d miic pixel theo hudng tiep can raster nhu hau het cac giii thuat phin doan chi dung cic thudc tfnh nhu miic xim trung binh, phuang sai va dp hgp hudng (coherence) m i theo hudng dua them cic dau hieu mdi ciia hudng tiep can vector nhu dp dii, dp cong va chi sd nang lugng ciia cac doan da tuyen bien de xii ly tich viing van chat lugng cao khoi viing nen v i viing nhieu tren tirng ngdn. Thuat toin de xuat tuy nhien cd tinh tong quit khdng chi ung dung dugc cho cic loai chi bin van tay giay, mi cdn cho c i vin tay sdng vdi nhieu loai bd cim nhin khac nhau.

De dinh gii, CSDL FVC2004 DB2 va CSDL C@FRIS DB gom 1000 man chi bin thuc te chpn ngau nhien tir tang thu can cudc can pham dugc dung de udc lugng cic phan bd xic suat ca bin phuc vu xiy dung bd phan loai Bayes va sau dd thir nghiem giai thuat phan doan de xuat. Ket qui thu nghiem cho thay giii thuat de xuat boat ddng hieu qui, dat do

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GlAl THUAT PHAN DOAN ANH CHI BAN VAN TAY MUOI N G O N 255 chinh x i c cao v i cd the d u a v i o ung dung thuc te de nang cap phan mem n h i p chi b i n hien

dang p h i i diing phucmg p h i p phan doan t u a n g t i c .

Bd cue bii b i o nhu sau: Muc 2 vdi cic ndi dung p h i t bieu bai toan phan doan chi b i n mudi ngdn, tong quan cic hudng tiep can lien quan va de xuat giai thuat p h i n doan chi b i n v i n tay mudi ngdn vdi hai cdng doan phan doan cat i n h thd v i phan doan min. Muc 3 l i phan thuc nghiem, d i n h gii v i sau cimg la phan ket luan.

2. P H A T B I E U B A I T O A N V A G I A I T H U A T XU* LI P H A N D O A N CHI B A N 2.1. P h a t b i e u bai t o a n '

Bai toan phan doan chi b i n v i n tay mudi ngdn dugc p h i t bieu van tat nhu sau.

Cho dau vao la i n h chi b i n van tay 10 ngdn da cap xam (greyscale), dp phan giii 500 dpi, tieu bieu nhu Hinh 1 ( m i u dai dien cho chi b i n A7 va t u a A7). Hay xay dung giii thuat t u ddng cat t i c h tir i n h chi b i n v i n tay 10 ngdn dau v i o t h i n h 20 i n h dau ra rieng re cho tirng ngdn, bao gdm: 10 i n h cho 10 ngdn lin thudc phan gifra chi b i n va 10 i n h cho 10 ngdn an thupc phan dudi chi b i n , sau dd xii ly d i n h gii chat lugng chi b i n tren tirng ngdn va dua ket q u i dudi dang cic mat na chat lugng van tay (inh nhi phan, cd gia tri 1 tai vimg van chat lugng cao va cd gii tri 0 tai cic vimg nen va vimg nhieu, chat lugng thap). Hinh 1 the hien mdt ket q u i xir ly p h i n doan thd chi b i n 10 ngdn bang ky thuat chuin hda, lam tran, chuyen ddi nhi p h i n va dd bien dinh vi khung cat. Hinh 2 minh hoa mdt ket q u i p h i n doan min If tudng vdi cic diem d i e trung gii tren bien nam ngoii vimg x i c dinh da dugc loai bo.

P h i n doan i n h chi b i n 10 ngdn l i bii t o i n phiic tap. Ngay c i vdi chi b i n thu n h i n bang thiet bi v i n tay sdng, van de xir If tich ngdn tir bd chi b i n 4 ngdn an ddng thdi ciing dang l i mdt van de thdi su ma cic hang sinh t r i e hpc the gidi dang quan t i m . Cd nhieu t i c gii [22] da de xuat giii p h i p cho bii t o i n p h i n doan nay nham t i c h phan 4 ngdn an dong thdi thanh tirng ngdn rieng re de cai d i t phan mem lap van tay sdng trang bi cho cic tram dang ky, kiem tra thi thuc nhap cinh. Tuy nhien, so vdi bii t o i n phan doan chi b i n van tay sdng, bai t o i n p h i n doan chi b i n v i n tay tren giay phiic t a p b a n nhieu do su da dang ciia cic loai bieu man chi b i n giay d u a v i o su dung, nhat la cic loai man chi b i n giay phi chuan, lech chuan (Miu A7 v i t u a A7) ciia thuc te nude ta. Cic t i i lieu cdng bd Hen quan den bii t o i n cat thd i n h chi b i n 10 ngdn thanh 20 ngdn rieng re hien nay rat ft. Tren Internet cd the tim dugc mot sd bang sing che ciia My de cap den chii de n i y [9], [16] nhung nhiing sing che nay chi trinh bay nguyen If hoat ddng ciia thiet bi, khdng tim thay t i i lieu n i o dua ra phuang phap v i giii thuat xu If cat i n h tir m i u chi b i n 10 ngdn. Thuc te hien nay hau het cac he thdng n h i n dang v i n tay t u dpng tren the gidi, trong dd cd mdt sd he da dugc t h u a n g mai hda va nhap v i o sir dung d nude ta nhu he MORPHO AFIS, he AFIX TRACKER, chil yeu van dang diing phuang p h i p t u a n g t i c true tiep tren man hinh de cat i n h chi b i n v i n tay thanh cac i n h rieng re. He MORPHO AFIS yen can ngudi sir dung phii diing chupt de dinh vi cic tam v i n tay cdn he AFIX TRACKER thi hien thi mac dinh 10 khung liiiih c ho

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256 NGUYEN THI HUONG THUY, NGUYEN NGOC MINH, NGUYEN NGQC KY

10 ngdn de ngudi sir dung tiep tuc chinh sua. Do p h i i cat i n h t u a n g t i c , tdc dp nhap lieu ciia cac he nay cdn rat cham (chi dat cdng suat dudi rnirc 200 chi b i n / n g a y / t r a m ) .

2.2. D e x u a t giAi t h u a t p h a n d o a n t h d

Y t u d n g chii dap ciia giii thuat nay d u a tren viec dimg ky thuat tien xir If pho dung nhu chuan hda, lam t r a n i n h va chuyen doi anh chi b i n ve dang nhi p h i n sao cho cic diem thupc vimg v i n quan t i m cd gii tri bang 1 cdn c i c diem nen cdn lai co g i i tri bang 0. Sau dd tien hanh dd bien de t i c h cic vimg van tay ra khdi phan nen chi b i n .

De t h u c thi y t u d n g tren, t a de x u a t giii thuat lam t r a n va dd bien theo c i c budc sau.

Buoc 1: Xii If chuan h o i va lam t r a n i n h

1.1) Xu li chuan hod miic xdm dnh: Do i n h van tay thu nhan ban dau cd muc x i m p h i n bd khdng thuan nhat, cd mdt sd vimg tren chi b i n lan muc q u i d i m nen qua den, cd sd k h i c lai q u i nhat, q u i s i n g nen can p h i i dung ky thuat chuan hda i n h dia p h u a n g [13], t u c l i thay ddi miic x i m ban dau / ( x , y) trong tirng cira so i n h bang muc xam mdi A''(x, y) n h u sau:

Nix,y)^ <

.Vox ( / ( x , y ) - M ) 2 ^. ^^ ^ , ^

^ o + V ~ ^ ^ ' v d i / ( x , y ) > M IVo X iIix,y)-Mf ,. ^, , , ^

^0 - y ^ ^ \f' - , v d i / ( x , y ) < M

vdi / ( x , y) l i miic x i m ban dau tai diem (x, y), M = (l/it;2)cr^u(7), V = il/w'^)oyjiI - M)^

lan lugt la muc xam trung binh v i p h u a n g sai miic x i m udc lugng tren cua so kfch thudc w XW (phan thuc nghiem chpn w = 32), MQ, VQ lan lugt la miic x i m trung binh v i phuang sai miic x i m can chuan hoi, A''(x, y) l i miic x i m mdi sau chuan h o i . ( M Q , VQ cd the chpn tiiy y, nhung phan t h u c nghiem chgn MQ = VQ = 100). (Can luu y rang, neu 1 cua so v i n tay bat ky cd M == MQ, V ^VQ thi A^(x, y) = / ( x , y)).

1.2) Dirng ciia ^6 w x w diem anh quet lan lugt tir t r i i qua p h i i tir tren xudng dudi de thay the gii tri miic x i m i n h hien tai bang gii tri trung binh ciia c i c diem i n h tren cua so.

Chuyen doi i n h ve dang nhi phan, dimg ngudng la g i i tri rnirc x i m trung binh dia phuang, tfnh tren cua so w x w.

1.3) Tien hanh dd bien bang giai thuat do bien 8-lien thdng va xir H xap xi tuyen tfnh tirng doan [18] de bieu dien cac dudng bien thanh nhirng da tuyen bien khep kin. De tang hieu q u i giii thuat dd bien p h i t hien viing v i n , can chgn b u d c ludi phii hgp de lgc lay cic vimg van, loai bdt cic viing nhieu nhd. Phan t h u c nghiem t a se g i i dinh viing van be n h a t cd kich thudc 8 X 8mm va vimg v i n Idn nhat cd kich t h u d c 20 x 20mm nen b u d c ludi thich hgp dugc chan la 8mm.

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Hinh 1

Hinh 1 man chi b i n 10 ngdn dugc p h i n doan thd bang ky thuat chuan hda, lam tran, chuyen doi nhi phan v i dd bien de tfnh bao loi va dinh vi hinh chii n h i t ngoai tiep de cat i n h .

Buoc 2: Xir If ket q u i dd bien, x i c dinh da giac ngoai tiep viing v i n can cat.

2.1) Tfnh bao loi ciia tap dinh da tuyen bien vimg dugc chgn bang thuat t o i n Graham [23].

Sau dd tfnh hinh chir nhat ngoai tiep bao loi de x i c dinh cua so e i t i n h .

2.2) Kiem tra cua sd i n h vdi cic dieu kien rang budc: dien tfch tdi thieu, dien tfch tdi da, vi trf t u a n g ddi ciia khung hinh so vdi man chi b i n .

2.3) Kiem tra thii t u ngdn: Ndi dung cua viec kiem tra thii t u ngdn la dimg thuat t o i n ddi sinh v i n tay d i de xuat [21] de tien hanh ddi s i n h tirng v i n tay 10 ngdn viing dudi vdi tirng v i n tay 10 ngdn vimg giira chi b i n de d u a ra ket luan vi trf cic ngdn dugc lan cd diing thii t u bieu m i u qui dinh hay khdng.

2.4) Tfnh cic gia tri Xmm, ^min, -'^maxi ^max Ciia cic dinh bao loi dudng bien, tiic la hinh chir nhat ngoai tiep de dinh vi toa dp khung cat.

2.5) Hien thi v i xir If t u a n g t i c cic trudng hgp d i e biet nhu cic chi b i n lan thieu ngdn, lin sai quy each khdng t h o i man dieu kien tham dinh.

Buoc 3: Hien thi ket q u i dinh vi khung cat de tham dinh bang mat thudng va chuyen sang doan t u a n g t i c .

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2.3. De xuat gidi thuat phan doan min

Ket qui xu H do cdng doan thir nhat xuat ra li cac inh van tay dugc cat ra theo tirng ngdn dudi dang cat thd. Van de tiep theo can giii quyet la de xuat giii thuat phan doan min tirng anh van dau ngdn tay dugc cat bdc tach ra khdi mau chi bin 10 ngdn cung cac thdng tin lien quan nhu dudng bien ciia tirng van, vimg trung tam, chieu hudng. Y tudng chii dao ciia giii thuat' phin doan min li phin tfch, tim cac thudc tfnh cd gii tri de nhan biet, dinh gii chat lugng cic vimg van chat lugng cao de tir dd dua ra ket qui dudi dang mot bin do hay cdn gpi la mat na chat lugng vdi gia tri 1 tai cac cua so ti; x it; dat chat lugng cao va gii tri 0 tai cic cua so w x w nen v i nhieu.

a) Qii ban goc

b) Sau khi phdn doan, loai bo cdc die &^m chi tiet tren bien

Hinh 2

Hinh 2, mdt chi bin dugc phan doan li tudng, vimg vin chat lugng cao dugc tach chinh xac, cic diem die trung tren bien va tren vimg nen thira dugc tu ddng loai bd.

Trude het can lam rd the nao la vimg van chat lugng cao. Mdt each true quan, dd la cic vimg van tren dd cd the phin biet rd cic ddng van va ddng ranh xen ke chay song song vdi nhau. Nhan biet ciia so van chat lugng cao la bai toan phin loai hai ldp, ndi dung chu yeu ciia bii toin phan doan min da dugc nhfeu tic gii quan t i m nghien ciiu. Can day nhat, Mohammad va Mohsen [17] da khio sit mdt loat cic phuang phap nhu phuang phap nhin biet vimg vin quan tam dimg hai thupc tfnh gii tri miic xim trung binh v i phuang sai, phuang phip phan doan theo bao ldi inh bien, phuang phap dimg ngudng dpng va phuang phap thfch nghi, sau dd de xuat thuat toan tren ca sd cii bien phuang phap ket hgp sir dung cic thupc tinh nhu dp hgp hudng (coherence), gii tri miic xam trung binh, phuang sai va cudng do miic xim ciia Bazen v i Gerez [1] bang each thay the thudc tfnh coherence bang mdt thudc tfnh khic tuang tu la hudng chii dao ciia dudng van tren ciira so lu x it;. Cieh tiep can niy tuy da cd cii tien han trude nhung van dirng lai d cieh tiep can raster, chi tap trung xu If tirng pixel inh m i khdng khai thic het die trung hudng ciia dudng vin.

Mdt tinh chat quan trpng ciia vimg vin chat lugng cao la sau khi xir If vecta hoi dudng bien va xap xi tuyen tfnh tirng doan, ket qui thu dugc li cac da tuyen gdm cac doan thang thanh phan cd dp dai Idn Hon nhieu so vdi budc vin, doi hudng cham va on dinh. Ngugc lai, cic viing vin chat lugng thap, thudng cho ra ket q u i la nhirng da tuyen gdm cac doan

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GlAl THUAT P H A N DOAN ANH CHi BAN VAN TAY MUOI N G O N 259 thang t h i n h phan ngan, thay doi hudng nhanh. Tir ket q u i p h i n tfch tren, ngoai cic thupc

tfnh truyen thdng nhu Mean, Variance ta de xuat bo sung them ba chi tieu mdi de n h i n dang cic khdi viing v i n chat lugng thap. Chi tieu mdi thii nhat la mat do D. chi tieu mdi thii hai la tdng do cong C va chi tieu thii ba la n i n g lugng E the hien su thay ddi do cong cua cic dinh diem ciia cic da tuyen tren ciia so it; x it;.

Mat dp D l i mat dp cic dinh ciia cic doan ngan ciia cic da tuyen dudng van di qua khdi It; X It), dugc d i e trung bang sd lugng dinh trong khdi dd.

Do cong tai mdt dinh da tuyen dugc do bang gia tri gdc doi hudng cua da tuyen tai dinh dd. Dp cong C ciia khdi bang tong dp cong cua cac dinh trong khdi dd.

Nang lugng tai mot dinh da tuyen dugc do bang gii tri chenh lech dp cong ciia da tuyen tai dinh dd so vdi dinh ngay trude nd. Nang lugng E ciia khdi bang tong nang lugng ciia cic dinh trong khdi dd.

G i i sir t a cd da tuyen {P}^ = {(xi, yi, ai), (x2, y2, ^2), •••, (xn, ym Qfyv), khi do dp cong tai dinh Pi v i dp cong ciia khdi w x w dugc dinh nghia nhu sau

C(PO = ( a ^ - a i - l ) , ^ = 2...iV, (2) Cwxw = / _, C ( / ^ ) , (3)

wxw

va nang lugng tai dinh Pi va nang lugng ciia khdi wxw dugc dinh nghia nhu sau

EiP) = CiP) - CiP.i), i = 2..7V, • (4)

E^xv^ = ^ EiP,). (5) wxw

Nhu vay, mdi khdi wxw dugc bieu dien bang mdt vecta gom 5 thanh phan nhvr sau

X^^,, = iM,V,D,C,E). (6) De phan loai tirng cua so w x w thudc ldp ui "vimg chat lugng cao" hay ldp u>2 "vimg

chat lugng t h a p v i nen", ta dimg bd phan loai Bayes diing qui tac quyet dinh tdi uu vdi h i m phan biet sau

giuj^) = Piuj^).PiX/u^),i = l,2. (7) Qui t i e p h i n ldp cu the nhu sau

IFigiuJi) > giL02)) THEN (X^,^^, e u;i) ELSE (X^^y, e ^2), (8) d day, Piu)2) = 1 — P(u;i); Pii^i) la tan s u i t xuat hien cira sd v i n tay chat lugng cao v i

PiuJ2) la tan s u i t xuat hien cua sd v i n tay chat lugng thap.

Cdng thiic udc lugng cic p h i n bd x i c suat n i y nhu sau (Tong cac khdi wxw thudc ldp CJ,)

P\U}l) = ; ; ^^ -, i = I, 2. (9) (Tdng c i c khoi wxw t o i n van tay)

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PiX/uJi) = (Tan suat xuat hien vector thudc tfnh X tren ldp Ui, i = 1, 2) d u g c x i c dinh qua giai doan udc lugng thdng ke hay hpc tren CSDL cac khdi v i n chat lugng khac nhau trfch chpn tir CSDL mau chi ban thii nghiem. Cdng thirc udc lugng n h u sau

P^X/uJi) = Tong c i c u; X It; cd Xw^w — N

,1 = 1,2. (10) T o n g sd u; X It; thudc u)i

Tir dd t a co giai thuat p h i n doan min dugc de xuat n h u sau.

Buoc 1: Tiep n h i n i n h v i n tay dau vao, la ket q u i x u a t ra tir cdng doan thd. Tiep nhan i n h dau vao l i i n h v i n dau ngdn tay cimg cac thdng tin phu t r g Hen quan n h u dudng bao, vimg trung tam, chieu hudng (tren/dudi).

Buoc 2: Chuan hda, l i m t r a n va chuyen ddi nhi p h i n . Dung ngudng dia p h u a n g v i chuyen doi i n h ve dang nhi phan.

Buoc 3: Vecta h o i bien i n h nhi phan va xap xi tuyen tfnh tirng doan.

Xii If dd bien dudng van, xap xi tuyen tinh tirng doan bang giii thuat da de x u a t d [19,20];

Ket hgp tinh do cong, n i n g lugng tren tirng dinh da tuyen, va tinh cac thuoc tfnh D, C, E.

Buoc 4- Phan loai cic khdi pixel wxw.

4.1) Dimg cua so kfch thudc phii hgp it; x io = 32 x 32pixels de duyet i n h gdc v i tfnh cic gia tri M, V de x i y dung vecta bieu dien Xyjxw = (-^i V: D, C, E).

4.2) Dimg qui tac quyet dinh tdi uu Bayes de xep X^jxw vao ldp t u a n g ung.

4.3) Ket q u i cho ra mat na chat lugng, l i dang i n h nhi p h i n cd g i i tri 1 tai khdi vimg v i n chat lugng cao va gii tri 0 tai nen va vimg v i n chat lugng t h a p .

a) Anh dii ban sau khi lam tion d i u y ^ d5i b) Chi bin sau khi vecto hoa d i u y ^ v6 ve dan g nhi phan dang da tuy^n

Hinh 3

Hinh 3, mat dp dudng v i n ngan, p h u a n g sai hudng cao, do cong thay doi dot ngpt la nhirng d i e trung cd gia tri de nhan biet vimg van chat lugng t h a p .

3. T H I J C N G H I E M 1. Kich b i n

a. Chgn cic mau chi b i n tieu bieu tir tang t h u can cudc can pham va t i n g t h u can cudc cdng dan de lap thanh CSDL C@FRIS DB gdm 1000 man chi b i n phuc vu t h u nghiem thuat t o i n phan doan thd.

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GlAl T H U A T P H A N DOAN ANH CHI BAN VAN TAY MUOI NGON 261 b. Chgn CSDL 500 ket q u i phan doan thd tir CSDL C@FRIS DB de thii nghiem thuat t o i n

p h i n doan min.

c. Chgn CSDL FVC2004 DB2b bao gom 500 chi b i n de thii nghiem thuat t o i n phan doan min.

d. So s i n h ket q u i p h i n doan ciia giii thuat de xuat vdi cic giii thuat truyen thdng chi dimg cic thudc tfnh M, V va Coherence, va vdi ket q u i phan doan ciia phan mem thuang mai Verifinger ciia hang Neurotechnology.

2. Ket q u i t h u nghiem thuat t o i n p h i n doan thd

e. Sd lugng chi b i n p h i n doan tdt, khdng can su can thiep ciia con ngudi: 973/1000.

f. Sd chi b i n diing qui cieh nhung giii thuat t r i lai khdng phan doan dugc: 0/1000.

g. Sd chi b i n sai qui cieh p h i i t r i lai: 27/1000, trong do 22 chi b i n dimg giay nen q u i tdi, 5 chi b i n cd cic van tay lin chdng len nhau, chong len khung.

3. Ket q u i t h u nghiem thuat toan phan doan min

Giii thuat phan doan min dugc d i n h gii tren 500 chi b i n CSDL FVC2004 DB2 v i 500 chi b i n tir CSDL C@FRIS DB dugc cat ra tir giai doan phan doan thd.

De luyen thuat t o i n p h i n doan, tirng v i n tay tren CSDL thii nghiem dugc p h i n chia thanh cic khdi pixel kfch thudc 32 x 32 de tfnh bd 5 cic dau hieu d i e trung. De dan giin cho viec udc lugng p h i n bd x i c suat, tirng dau hieu dugc p h i n khoing gii tri nhu sau: Dau hieu M, F:100 khoing; D: sd lugng dinh diem: [0, 20]; Dau hieu C, E : [-60 khoing, +60 khoing], mdi khoing 3 do.

Hinh 4 minh hga mpt sd ket q u i xir li p h i n doan min tieu bieu cic m i u v i n tay chat lugng thap chpn tir CSDL FVC2004 DB2.

4. K E T L U A N

• Ddng gdp chfnh cd y nghia ciia cdng trinh n i y la da de xuat giii thuat t u ddng p h i n doan i n h chi b i n 10 ngdn theo hai giai doan thd va min d u a tren hudng tiep can vector v i su dung hai thudc tfnh truyen thdng (Mean, Variance) va ba thudc tfnh de xuat mdi dd l i mat do cic doan ngan, do cong v i chi sd n i n g lugng ciia cac dinh chu tuyen (Density, Curvature, Energie).

Qua t h u nghiem giii thuat p h i n doan thd de phan doan chi b i n 10 ngdn tren CSDL chi b i n giay tieu bieu, ket q u i dat dugc do chinh x i c cao, tdc dp xir If nhanh, sd chi b i n phii t r i lai de can thiep thii cdng rat ft, chiem ty le chi dudi 2,7%.

Giai doan phan doan min dimg ky thuat dd bien va n h i n biet chat lugng viing van dua tren viec d u a them thudc tfnh mat dp doan v i n ngan, dp cong v i chi sd n i n g lugng dudng bien rdi sau dd diing qui tac quyet dinh tdi uu Bayes de p h i n ldp chat lugng viing vin la mdt hudng tiep can mdi the hien dugc tinh hieu q u i vugt trdi so vdi cic giii thuat khac chi diing gia tri trung binh muc x i m M , phuang sai V va dp hgp hudng Coherence. Khi so sinh ket q u i phan doan vdi phan mem Verifinger thudc tdp 5 dan dau te gidi hien nay, ket q u i

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phan doan ciia thuat toan de xuat dua ra la phii hgp vdi ket q u i ciia Verifinger. Nhirng vung thuat toan de xuat dinh gii chat lugng cao thi phan mem Verifinger ciing danh gia cao. Cac inh vin tay phin doan ciia Verifinger ro net ban chii yen la nhd khau tien xu If anh trude khi tien hanh vector hda khdng thudc pham vi xii If ciia thuat giii thuat phan doan.

a) Anh dia't luang tha'p b) Kfft quS phan doan theo M.V. Cohenrence va vecto hoa ^nh g6c

c) K^t quS phan doan Cll a thuat toan d6 xuSft dilng (M.V J),C,E)

d) K6t qui phan doan cua thuat toan Verifinger

Hinh 4

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GiAi THUAT PHAN DOAN ANH CHI BAN VAN TAY MUOI NGON 263 Tren Hinh 4 li ket qui phin doan mdt sd inh chi bin chat lugng,thap, chpn tir CSDL FVC2004.

•«15'*U.

a) Anh chat luong tha'p b) Ket qua phan doan c) Ket qua phan doan theo M.V. Cohenrence c u a t h u a t toan d^ xuit va vecto h6a i i h g6c dting ( M . V J J . Q E )

Hinh 5

d) Kft qua phan doan cua thuat toan Verifinger

Hinh 5 minh hga mdt sd ket qui xir li phin doan min tieu bieu cic man van tay chat lugng thap chpn tir CSDL C@FRIS DB.

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2 6 4 NGUYEN THI HUCTNG THUY, NGUYEN NGOC MINH, NGUYEN NGQC KY

U'u diem chinh ciia giii thuat mdi d u a tren viec p h i n tfch ket h g p c i c d i e t r u n g vung vdi cac d i e t r u n g chu tuyen bien la cd the ket hgp ddng thdi vdi q u i trinh trich chpn diem d i e trung. Viec ket h g p ddng thdi vira dd bien trich chpn diem dac t r u n g theo dd cpng, vira phan doan min, vira d i n h gii, sang lgc c i c diem d i e t r u n g chi tiet cho phep tiet kiem thdi gian tinh t o i n v i n i n g cao hieu q u i xir If r a t dang ke.

C i c ket q u i p h i n doan thd va min dat dugc, bao gdm cac thdng tin c a b i n n h u dudng bien, t a m d chi b i n , m a t na chat lugng la nhung t h a m sd r a t quan trpng dung de d i n h gii dp tin cay c i c diem d i e t r u n g va n i n g cao hieu q u i thuat t o i n ddi s i n h . C i c giai thuat de x u a t b u d c dau da dugc dimg de cai dat nang cap he n h i p lieu cho he nhan dang van tay t u ddng C@FRIS ciia Phdng Thf nghiem Md phdng va Tich h g p he thdng thudc Tong cue Hau can Ky thuat, Bd Cdng an.

T A I L I E U T H A M K H A O

[1] A. Bazen and S. Gerez, Segmentation of fingerprint images, Proc. Workshop on Circuits Sys- tems and Signal Processing ProRISC, Veldhoven, Netherlands, 2001 (276-280).

[2] A.B. Xuefeng Liang and T. Asano, A near-linear time algorithm for binarization of fingerprint images using distance transform. Combinatorial Image Analysis L N C S 3 3 2 2 (2004) 197208.

[3] C. Wu, Z. Shi, and V. Govindaraju, Fingerprint image enhancement method using directional median filter, Biometric Technology for Human Identification, SPIE 5 4 0 4 (2004) 66-75.

[4] C.Wu, S. Tulyakov, and V. Govindaraju, Image quality measures for fingerprint image enhancement, International Workshop on Multimedia Content Representation, Classification and Security(MRCS) volume L N C S 4105(2006) 215-222.

[5] E. Zhu, J. Yin, C. Hu, and G. Zhang, A systematic method for fingerprint ridge orientation estimation and image segmentation. Pattern Recognition 3 9 (8) (2006) 1452-1472.

[6] E. Lim, X. Jiang, and W. Yau, Fingerprint quality and validity analysis, IEEE International Conference on Image processing (ICIP) 1, Rochester, New York, USA, 2002 (469-472).

[7] E. Tabassi and G. L. Wilson , A new approach to fingerprint image quality, IEEE International Conference on Image processing (ICIP) 2, Genoa, Italy, 2005 (37-40).

[8] F. Alonso-Fernandez, J. Fierrez-Aguilar, and J. Ortega-Garcia, An enhanced Gabor filter-based segmentation algorithm for fingerprint recognition systems. Proceedings of the 4th Interna- tional Symposium on Image and Signal Processing and Analysis (ISPA 2005), 2005 (239- 244).

[9] Hara, Fingerprint Image Cutout Processing device for tentprint card. US patent No. 6282302.

Date of Patent: Aug. 28, (2001).

[10] J.Yang, L. Liu, T. Jiang, Y. Fan: A midified Gabor filter design method for fingerprint enhancement. Pattern Recognition Letters 24 (2003) 1805-1817.

[11] K. Uchida Image-based approach to fingerprint acceptability assessment, ICBA, (2004) 294-300.

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GlAl THUAT P H A N DOAN ANH CHI BAN VAN TAY MUOI N G O N 265 [12] K. Lee, S. Prabhakar, "Probabilistic Orientation Field Estimation for Fingerprint Enhancement

and Verification", Proceedings of the 2008 Biometrics Symposium (BSYM), Tampa, Florida 23-25 September 2008, 41-46.

[13] L. Hong, Y. Wan, Anil K. Jain, Fingerprint Image Enhancement: Algorithm and Performance Evaluation, P a t t e r n Recognition and Image Processing Laboratory Department of Computer Science Michigan State University, East Lansing, (2004) MI 48824.

[14] L.Wang, H. Suo, and M. Dai, Fingerprint image segmentation based on Gaussian-Hermite mo- ments. In Advanced D a t a Mining and Applications, LNCS3584, (2005) 446-454.

[15] L. Shen, A. Kot, and W. Koo, Quality measures of fingerprint images, Preceding 5^ Interna- tional Conference on Audio and Video-Based Biometric Person Authentication (AVBPA), Spring LNCS-2091, 2001 (266-271).

[16] Maase, Device and method for obtaining a plain image of multiple fingerprints, US patent No.

5650842. Date of Patent: July. 22, (1997), http://www.freepatentsonline.com/5650842.htmL [17] Mohammad Sadegh Helfroush and Mohsen Mohammadpour, Fingerprint Segmentation, World

Applied Sciences .Journal 6 (3) (2009) 303-308.

[18] Nguyen Ngoc Ky, Nghien cuu, thiet ke va cai dat He bieu dien va dong nhat van tay CAFRIS,

"Bao cao ket q u i nghien cuu de tai NCKH cap Bo va cap Nha nude KC-01-08", (1995).

[19] Nguyen Ngoc Ky, P h u a n g phap bieu dien cau triic ky t u theo hudng tiep can vec-to, Tgp chi Tm hgc vd Dieu khien hgc 1 6 (1) (2000) 72-79.

[20] Nguyen Ngoc Ky, Bieu dien va ddi sanh i n h d u d n g net ket q u i nghien ciiu phat trien cong nghe, ling dung trong Hnh vuc nhan dang van tay, chir viet va nhap dir lieu dd hoa, Ky yeu hgi nghi CNTT CAND, Ha Noi, thang 9 nam 2001.

[21] Nguyen Thi H u o n g Thiiy, Nguyen Ngoc Minh, Nguyen Ngoc Ky, Hoang Xuan Huan, Thuat toan nang cao hieu q u i ddi sanh van tay dimg md hinh bien dang dia phuong. Hoi thdo Quoc . gia lan thu 4 (FAIR2009): Nghien ciiu co bdn vd ung dung CNTT, Dai hoc Cdng nghe,

Dai hoc Qudc gia Ha Noi, 25-26/12/2009.

[22] Robert Hold, Surinder Ram, Horst Bischof, and Josef A. Birchbauer, Slap fingerprint segmentation, Computer Vision Winter Worshop 2009, P R I P Vienna University of Technology, Austria, February 4-6, 2009.

[23] R.L. Graham, An efficient algorithm for determining the convex hull of a finish planar point set.

Information Processing Letter 1 (1998) 226-239.

[24] S. Klein, A. M. Bazen, and R. Veldhuis, Fingerprint image segmentation based on hidden markov models, 13' Annual workshop in Circuits, Systems and Signal Processing, Proc. ProRISC, Veldhoven, Netherlands, 2002 (310-318).

[25] X. Chen, J. Tian, J. Cheng, and X. Yang, Segmentation of fingerprint images using linear classifier, EURASIP Joumal on Applied Signal Processing (4) (2004) 480 494.

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[26] Y. Chen, S. Dass, and A. Jain, Fingerprint quality indices for predicting authentication performance, Proc. of International Conference on Audio and Video-Based Biometric Person Authentication (AVBPA), Rye Brook, NY, 2005 (160-170).

[27] Z. Yuheng and X. Qinghan, An optimized approach for fingerprint binarization, Proc. of the International Joint Conference on Neural Networks (IJCNN), part of the IEEE World Congress on Computational Intelligence, Vancouver, BC, Canada, 2006 (391-395).

Nhgn bdi ngdy 5 - 5 - 2010 Nhgn lgi sau sua ngdy 30-8 -2010

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