                           ˿µϣ20091109գ

09.11.09, Ƶй˵ġŵ֮Ρ
09.11.09, ԺüϸˡФҽڵѧ쿴ɡ
09.11.09, ǧۡФںľѧԺΪ
09.11.09, ɡһҽԺզôֱ׳
09.11.09, wenxiagongӱڵҽƾԤйҽƼҽƽӹ죡
09.11.09, °ZJѧôԴƽҲôء
09.11.09, ǡѧѧԺĹͣʮߣڱѧѧ
09.11.09, ̤ʵɽˡй˹ѧ¡ѧϰרί᳣ίԱɽѧѧϮԡ
09.11.09, XiaoϺѧѧԺȫĳϮġ
09.11.09, ʷţڲQQԽڿΡƾѧһݹʾְϽ
09.11.09, Kolmogorov־¼Ľһ롷
09.11.09, οѡԼPerroneCooperĹ
09.11.09, ףƽ
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09.11.09, Сݡ۳ǴȻпԺԺʿͽڡ
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09.11.09, ëϯǮѧɭͬ־̸
09.11.09, ɽ֮ʯġǮѧɭ20ʴиСһĵ߼
09.11.09, KENûơ
09.11.09, ˡ˵˹̹۲׼ȷ
09.11.09, ѧѧа񹫲ڵ18ѧϰ

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Ƶй˵ġŵ֮Ρ

http://you.video.sina.com.cn/b/25817095-1589298705.html

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ԺüϸˡФҽڵѧ쿴ɡ

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ϸڡФҽڵѧ쿴ɡᵽĵڶĵ㣬
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ԺȻܹĿ޳Ʊһϣ൱ġ
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绰λĿ̧֣Ժ˻ѧԺ
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ФˣϼݴѧȫְڣľԺʱĿ
ȷΪ˼ǿԺϵĿмʵûְľԺһԺ֮
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һҽԺզôֱ׳

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ӱڵҽƾԤйҽƼҽƽӹ죡

ߣwenxiagong

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Ѫ˨γĿǰкܴ顣һ㲻ʹÿѪҩΪѪҩ
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5, Ҳ䡭

ϣҽԺcctvҵĹ˾йҽƽй
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ZJѧôԴƽҲô

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ѧѧԺĹͣʮߣڱѧѧ

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ѧѧԺùѧԼ¡ʵѧ
ѧڱѧѧԺΪҳϵϿĿǰѧ
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ѧԺͬ꣬޷ѣעֱ档

֮˵ѧԺ޹ؽҪΪʷ֪
ѧԺ֮ǰߵöࡣTimes Higher EducationΪ
2004ǣ

	ѧ	
2004		10
	廪	15
2005		10
	廪	17
2006	廪	14
		20
2007	廪	16
		36
2008	廪	12
		38
2009	廪	13
		31

ɼ廪ȶʮλãӹѧԺ֮
ʹӵʮ˵ʮ֮¡⣬ӵ÷ѧһֱ
50ң廪һֱ60ҵһΡ

ۣѧԺѧѧϺȣԼ֪ܵԴΪ١



Դhttp://www.coe.pku.edu.cn/subpage.asp?id=1862

ѧѧ ѧǰéǰé

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

ʱ:2009-10-30 17:33:24:476 
 
    ݡź籨2009618շ ̺ͼ
ôѧѧλе38λӢ׶Times Higher 
Education-QS World University Rankings¹2009ȡ̺Ϣ
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top50ĶǰéΪȫѧˣֹǧ١
 
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š1948͡籨ϲ籨1983
ʼѧԺϵнϸߵ֪ȡ
 
    άٿTimes Higher Education: Times Higher Educationһ
רűߵȽصż¼־ܲλ׶ء1971
һڿʼһֱԱֽʽ棬ֱ2008110ոΪ־
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귢µҲTimes Higher EducationΪ֪
 
    ӰĴѧУѧй½Ĵѧйѧ
ڶڡй½ĴѧУڱѧǰ廪ѧ
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ѧΪһѧѧԺΪһѧԺŬ
 
Us News and World Report:
http://74.125.153.132/search?q=cache:W1xdzp8hHFEJ:www.usnews.com/articles/education/worlds-best-colleges/2009/06/18/worlds-best-colleges-engineering-and-it-universities.html%3FPageNr%3D1+US+news+and+world+report+Peking+University+38&cd=2&hl=en&ct=clnk
 
Times Higher Education:
http://www.timeshighereducation.co.uk/WorldUniversityRankings.html

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й˹ѧ¡ѧϰרί᳣ίԱɽѧѧϮ

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㷨Ͼѧѧ(Ȼѧ) 39(4)
[11]ղС, ±, , , 2003һָĽĵģʽָƥ
ϾѧѧԿư棩94
[12]ҵ ±  2003ָͼϸ㷨оϾ
ѧѧԿư棬394ڣ
[13]ղС ±  ̷̨ ̣2003༶ֿߴµָ
Ϣȡ㷨Ͼѧѧ(Ȼѧ)39(4)
[14]20046£ָ߾㷨ۣ
ģʽʶ˹ܡ2
[15], , , 2004.10ڴ󴰿Ƶ׷
ָ߾Ʒ,ѧ(Ȼѧ)Vol. 43 No. 5
[16]źΰ2005Delaunayǻָƥ䷽
о뷢չ42(9) 
[17]Ning Liu, Yilong Yin, Hongwei Zhang2005A Fingerprint 
Matching Algorithm Based On Delaunay Triangulation NetProceedings of 
the 2005 The Fifth International Conference on Computer and 
Information Technology (CIT05)0-7695-2432-X/05  IEEE
[18]̷÷ ,  , ԣ20059£ˮƽָ߾
Ʒִѧѧ( ѧ) Vol. 35 No. 5  
[19]Xiaosi Zhan, Zhaocai Sun, Yilong Yin, and Yayun Chu2005
Fingerprint Ridge Distance Estimation: Algorithms and the Performance
Lecture Notes in Computer ScienceSpringer Berlin / 
HeidelbergVolume 3832/2005p294-301
[20]Ϊ ,,2005һֻˮƽ߾Ʒɽ
ṤҵѧԺѧ,2005/04
[21]Ϊ,,2005һֻƵ׷ָ߾
ɽѧѧ(ѧ)20054 

ƪصһ [1][16]ƪģ

[1]ԭעո1999 621ա1999 ֮ǰָʶ
оͼѷǳ졣ͳо̽ݷָƵһ
Щָ߼ľ롢Ƕȡȣ飬ȡúܺЧ
ϢķչǿʼÿѧЩйȡ
ѧģͣʹΪ˹еһҪ֧ʵеõָƣ
ΪڷЩָƽԤʹָԤ
ָʶһǳҪо[1]ָԤ[1]ҪϮ
ƪ£

[Lin 1]Lin Hong, A.K. Jain, S. Pankanti, and R. Bolle, 1996. 
Fingerprint Enhancement,Proc. First IEEE WACV, pp. 202-207, 
Sarasota, Fla.,
[Lin 2] Anil JainLin Hong, and Ruud Bolle, 1997,On-Line 
Fingerprint Verification Anil Jain, Fellow, IEEE, Fellow, IEEEIEEE 
TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 19, NO. 
4, APRIL 
[Lin 3]Lin Hong, WAN YF, JA IN, 1998, A. Fingerprint image 
enhancement: algorithm and performance evaluation [J]. IEEE 
Transaction on Pattern Analysis and Machine Intelligence, 20 (8): 777 
- 789.

[1]Ĳοֻƪ˶ʿĺһƪ־£[1].
һָԶȡ㷨о: [˶ʿѧλ] .ͻ
еѧԺ, 1997[1]ΰ,е.ָԶʶϵͳеԤ.
չо. 1997, 6(34)[1].ָͼϢо: [˶ʿѧλ
].:廪ѧ, 1995. 25~28[1]Ƚ[1]еԤƽ
[1]еRaoĸĽ㷨ֱַȡ[1][
1]˲Ǵ£ֻ׽ܡ[1]Ĵp111Ļ˵
ڳоָͼϢȡĻ,һȡָͼ
Ϣ·ͿǷ㷨

[1]㷨6ǰ2ԭ£

(1)ָͼ񻮷ΪصĴСΪwwĿ,ԷֱΪ500 dpiָ
ͼ,ʼֵΪ1616
(2)ָͼǿ,ÿһصһƫ,ݼҪ,
һƫӿѡ򵥵SobelӻӵMarr-Hildrethӡ
(1)е500 dpiָͼֱΪ1 Ӣ500ص㣬FBIķֱ
ʣϸ[Lin 3]p779

Ϯ[Lin 3]p780~781ԭ£

1) Divide normalized image into blocks of size w w (16 16).
2) Compute the gradients ?x(i, j) and ?y(i, j) at each pixel, (i, 
j). Depending on the computational requirement,
The gradient operator may vary from the simple Sobel operator to 
the more complex Marr-Hildreth operator
[13].ע[13].[Lin 3]ĲοףΪD. Marr, Vision. San 
Francisco, Calif.: W.H. Freeman, 1982.

Ӣĺ[1]ԱȣȻ[1]㷨(1)2ȫȡ
[Lin 3][Lin 3]ȷصһƫSobelӻӵ
Marr-HildrethӣָԲο[13]

ٿ[1]p1113ԭ£

3ÿͼķϢʽͼ1

ͼ1    [1]p111ʽͼ                       ͼ2   [Lin 3] p781
Ĺʽͼ

ʽ  ?xf(i,j) ?yf(i,j)(i,j)xyһƫ

Ϯ[Lin 3]p781 ԭ£ע[Lin 3]p781ʽӡˢ
˹ʽȡ[Lin 1] p4

Estimate the local orientation of each block centered at pixel (i, 
j) using the following equations [17]ͼ2[17][Lin 3]Ĳο
[17]£
[rao1]A. Rao, 1990.A Taxonomy for Texture Description and 
Identification. NewYork, NY: Springer-Verlag, 

ͼ12Աȿ[1]p111ʽ[Lin 3] p781Ĺʽʽͬ
кarctanķӺͷĸıʽͬҪж[1] p111ʽ
Ĵ»ˣҪҵùʽԴùʽ Kass 1987A. 
Rao, 1990Bazen 2002˽ͺЩǣ

[Kass 1]M. Kass and A. Witkin, 1987. Analyzing Oriented 
Patterns, Computer Vision, Graphics, and Image Processing, vol. 37, 
no. 4, pp. 362-385,
[rao2] A.R. Rao, 1990.A Taxonomy for Texture Description and 
Identification. NewYork, NY: Springer-Verlag, 
[rao3] A.R. Rao1991Computing Oriented Texture Fields CVGIP: 
GRAPHICAL MODELS AND IMAGE PROCESSINGVol. 53, No. 2, March, pp. 
157-185, 1991
[Bazen 1]A.M. Bazen, S.H. Gerez, 2002Systematic methods for the 
computation of the directional fields and singular points of 
fingerprints, IEEE Trans. Pattern Anal. Machine Intell. 24 (2002) 905
C919.p907

[Bazen 1]p907Ըùʽ˵

Gradients cannot directly be averaged in some local neighborhood 
since opposite gradient vectors will then cancel each other, although 
they indicate the same ridge-valley orientation. In [17](ע
ָ[Kass 1]), a solution to this problem is proposed by doubling the 
angles of the gradient vectors before averaging. After doubling the 
angles, opposite gradient vectors will point in the same direction and, 
therefore, will reinforce each other

[Bazen 1]˵úȷָ·ڷУΪͬ
һ˲ܽݶֱӽƽǶʿеݶƽ
лụΪ⣬Kass 1987ݶķȡ2
ݶģֵȡƽ[1] ?xf(i,j) ?yf(i,j) [Lin 3]G 
x(i,j) G y(i,j)ֱʾSobelӼx yһƫ
ȻʾŲһһͨһصݶȷ
ݶȷ㹫ʽΪ

(i,j)= arctan?yf(i,j)/?xf(i,j)(i,j)= arctanG y(i,j)/ G 
x(i,j))

ͼ12Կ[1]p111ʽ[Lin 3] p781ĹʽԷ
arctan1/2Ϊ[Bazen 1]˵ݶȡ2
ݶģȡƽƵսǷкarctanҪ1/2
Ƶ̼[Kass 1][Bazen 1]ﲻг[1]p111ʽȴֱ
صݶȽӣûнݶȡ2ݶģȡƽ
ͼ1䷽(i,j)ҲԷкarctan1/2õͼķ
ҪͼڵصݶȽƽ[Bazen 1]ȷ˵
ܽݶֱӽƽ[1]p111ʽȴֱӽصݶȽ
ȻƽȻ[1]p111ʽǸʽ

[1]p111ǶȵĹʽҲǴģ[1] p111ԭ£

(i,j)ķΧ-/4~/4֮,Ϊ㷨Ҫ,Ƕȵ
0~֮,´:
Vx(i,j)>0,ÿΪ0~/43/4~֮,(i,j)=
(i,j)+/2;
Vx(i,j)<0,Vy(i,j)>0,ÿΪ/4~/2֮,
(i,j)=(i,j)+;
Vx(i,j)<0,Vy(i,j)<0,ÿΪ/2~3/4֮,(i,j)

СǶȵ0~֮䡱еĽǶȣͼ1ʽ3еĦ
(i,j)(i,j) [rao3] P163Ϊ.Dominant direction[Bazen 1] p907Ϊ
gradient direction(i,j)ֻݶȷͼ鷽ҪټӦ/2
ȷĽǶȵʽǣȰ-/4~/4֮-/2~/2֮䣬ټϦ/2
õͼ鷽Χ0~֮䣬[1]ûŪԹʽǴġ
ȷĵʽͽͼ[Bazen 1] p907

[1]p112ĵ4ԭ£

ָͼԵṹϢȱԭ,ķ
ϢȷġָƵ·,ǻᷢһص:
ط,ھֲ,·仯һ㶼ǱȽϻġһص,
һͨ˲ԸָͼķϢƽ,׼ȷļ
ͨ˲ͼ3:

ͼ3 [1]ԭp112ʽͼ                      ͼ5 [Lin 3] p781
ʽͼ

ʽ hάͨ˲,wwΪ˲ߴ,˲ȱʡߴΪ55
ص

 [Lin 3]p781ԭ£

Due to the presence of noise, corrupted ridge and valley structures, 
minutiae, etc. in the input image, the estimated local ridge 
orientation, q(i, j), may not always be correct. Since local ridge 
orientation varies slowly in a local neighborhood where no singular 
points appear, a low-pass filter can be used to modify the incorrect 
local ridge orientation. In order to perform the low-pass filtering, 
the orientation image needs to be converted into a continuous vector 
field,which is defined as follows:

ͼ4   [Lin 3] p781Ĺʽͼ

where ? x and ? y are the x and y components of the vector field, 
respectively. With the resulting vector
field, the low-pass filtering can then be performed as follows
ͼ5:

һûг[Lin 1][Lin2]У[Lin 3]һĵĴ£ͨһ
ͨ˲Ե3õķǶȹˣȥ[Lin 3]ûֱ
ӶԽǶ˲ͼ4еĹʽǶתΪ
continuous vector field? x  ? yȻ? x ? y
תıҪ

[rao4]A.R. Rao, R.C. Jain, 1992"Computerized Flow Field Analysis: 
Oriented Texture Fields," IEEE Transactions on Pattern Analysis and 
Machine Intelligence, vol. 14, no. 7, pp. 693-709, July 1992 

P696ǿ[1]p112ȻҲ[Lin 3]õͨ˲ԽǶ
ˣȴֱӶԽǶ˲ͼ3ûתΪcontinuous 
vector fieldǹⲻȫѹʽдǳˣǺ
[1]ʽ˼·Ϯ[Lin 3]ʽǴġ [1] ô
ĹʽʵȻõ׼ȷָƷϢ[1]p112

ٿ[1]p112ĵ56ԭ£
(5)ͼϢĿɿԣʽͼ6

ͼ6 [1]p112ʽͼ                 ͼ7 [Lin 2] p305Ĺʽͼ
ʽ D(i,j)ΪĵĿΧһֲ,һֿͼļ,ȱʡ
ߴΪ55ص
nDڿĿ
(i,j)(i,j)(i,j)(i,j)ķ
(6)C(i,j)һԤ趨żֵTc, ֿߴ,½з
ϢֱҪ󡣵Ȼ,ֿߴļС,

[1]p112ĵ56ȫ̳ϮⲿֱϮûг
[Lin 3]ǳ[Lin 1]p4[Lin2]p305[Lin2]p305ԭ£

2. Compute the consistency level of the orientation field in the 
local neighborhood of a block (i, j) with the following formulaͼ
7:
where D represents the local neighborhood around the block (i, j) 
(in our system, the size of D is 5  5); N is the number of blocks 
within D; (i,j) and (i,j)are local ridge orientations at 
blocks(i,j) and (i, j), respectively.

[Lin2]ⲿһϴ£Wangµp825ᵽ

In order to measure the reliability of estimation for hs, Kass 
and Witkin [16] introduces a metric called coherence that calculates 
the strength of the averaged gradient in the distribution of local 
gradient vectors. Instead of using equal-sized blocks, Jain et al. 
[17] proposes a hierarchical scheme to adjust the estimation 
resolution of local orientation fields via iterative steps. They 
introduce the concept of consistency level, If the consistency 
level is above a certain threshold, the local orientations around the 
objective block are re-estimated with a smaller window size.μף
Yi Wang , Jiankun Hu, Fengling Han(2007) Enhanced gradient-based 
algorithm for the estimation of fingerprint orientation fields 
Applied Mathematics and Computation 185823C833

WangȷָΪȷĿɿԣKassWitkin1987
coherenceָ꣬[Lin2]һhierarchical·
consistency levelָָ꣬Ԥ趨żֵȽ, ظֱ
Ҫ󣬶[1] У[Lin2]Ĵ㷨ȻĴ¡

ٿ[16]ĳϮ⣬ĿΪDelaunayǻָƥ䷽
2005ڼо뷢չĺ㷨ԣ

[Parziale 1] Giuseppe Parziale and Albert Niel2004Fingerprint 
Matching Using Minutiae Triangulation Lecture Notes in Computer 
ScienceSpringer Berlin / HeidelbergVolume 3072/2004Biometric 
Authentication

1999꣬G. BebisнָʶӦDT 
Delaunay Triangulation

[Bebis1] G. Bebis, T. Deaconu, M. Georgiopoulos:Fingerprint 
Identification Using Delaunay Triangulation,ICIIS99, Maryland, Nov. 
1999.

[Parziale1]ܽ[Bebis1] ڵгɹĻϣDT 
ƥ㷨ָϸƥ䣬[Parziale 1]p3ᵽ

In our approach, the dependency among minutiae is obtained 
applying on the point set a Delaunay triangulation: each minutia is 
used as a triangle vertex. We use this approach, since the Delaunay 
triangulation was found to have the best structural stability under 
random positional perturbations [13].ע[13]ָ[Bebis1]

пԿDT õĽṹȶԡ㷨Ҫϸڵ
DT磬Delaunay ʷ㷨г㷨ڼ㼸
ֻҪռȶ㷨ϸڵʷּɣ[Parziale 1]û
ϸгһ[16]˾岽裬òǴµĹؼ¹ؼ
ƥ㷨

[16]p1624Ϯԭ£

DTľֲƥοԵȡDTľֲƥ㷨Ǵģָ
ƺʹʶָνṹ,õεĶΪο?
Ѱƽṹʱ,㷽򡢱ߵĳȡεڽǵȶõЧ,
ͼ4ʾͼ8

ͼ8 [16]p1624ͼ4ͼ                ͼ9 [Parziale1]p3ͼ1ͼ

[16]ͼͼ8ֱ[Parziale1]p3ͼ1ͼ9[16]
ڿ[Parziale1]p3ͼͼ9󣬰ͼֳͼabͼ8

[16]ڶͼ4ͼ8ж㷨

ͼTem,InDTƱ?иѡһǱ
L1,L2,ֱ߳Ϊl1,l2?L1˵R11,R12㷽ΪD11,D12,
L2˵R21,R22㷽ΪD21,D22,жǷ
ͼ10:

ͼ10   [16]p1624Ĺʽͼ               ͼ11   [Parziale1]p3
ʽͼ

[Parziale1]p3ͼ1ͼ11ж㷨

the distance L between the two minutiae;
the angle  between the orientations of the two minutiae (angular 
difference between i andj );
the angles1 and 2 between the orientation of each minutia and 
the segment connecting them.
Then, each minutia pair of the query set Q is compared with all 
the minutia pairs of the template set T, according the following 
relations:

Ƚͼ1011ɼͼ10Ĺʽ2ͼ11Ĺʽ5Ϊͼ
1011ԼͼиĽͲѿͼ11ʽ5еĦQͼ10ʽ
2е?D11D12?ͼ11ʽ5еĦTͼ10ʽ2е?D21
D22?

Q= ?D11D12?
T= ?D21D22?

ͼ10ʽ2ͼ11ʽ5һġͼ10ʽ1
ͼ11ʽ4ֻͼ11ʽ4minLQLTΪ1ɡͼ11ʽ
6[16]p1625Ĺʽ

ͼ12  [16]p1625Ĺʽͼ

[Parziale1]p3ֻһʽͺܾıȽʽ
дɶʽӡ

[16]ƾָƥ䲽裬ƾʽ[Lin 2] 
p308Ĺʽ[Parziale1]p2ĹʽﲻͣߵĹʽȡһ
֪

ͼ11  [16]p1625Ĺʽͼ                 ͼ13  [Lin 2] p308Ĺ
ʽͼ


ͼ13   [Parziale1]p2Ĺʽͼ

ָƥ䵱Ȼǰǰ泭[Parziale1]㷨ƥ䣬
p1625һƥԭ£
ģָÿһ㶼ʹʶָδõƥƥ
һ֮,ǵõһʶָеõƥĵN,M1=ģϸ
,M2=ʶָϸڵ,ƥ

Score = N/sqrt ( M1  M2 )?

ƥ[Parziale1]p4[Parziale1]ԭ

ͼ14[Parziale1]p4Ĺʽͼ

ʽһģһֻѧŲͬĩȾЩ
㷨ʵָһʵ֤˵ƪ£㷨ȫǳϮ
ǵĴ?ƪָĳӢģŮ˶ʿֳ˵
һߣ

Ning Liu, Yilong Yin, Hongwei ZhangA Fingerprint Matching 
Algorithm Based On Delaunay Triangulation Net1 Proceedings of the 2005 
The Fifth International Conference on Computer and Information 
Technology (CIT05)0-7695-2432-X/05 2005 IEEE

ϷЩ´Ƕ£22
ĹȻѧϮдֶƵЩûд
£ǳϮĵĳһֺ֣ܽƻ˿ý¶
ԭⲻسһ۾ͿЩͨķԼĻ
߰ҪοײгöҲܷ[1]˵[1]
[1]ķ˵ǰָͼϢȡоˮƽ ⲻ֪
[1]ᵽķȡ

[Mehtre1]B.M. Mehtre1993Fingerprint Image Analysis for 
Automatic Identification Machine Vision and Applications 6:124-139

[1]ͼ2Ҳֱȡ[Mehtre1]p125ͼ2[1]ķȡ[rao3]
p163[1][1]ķĴоˮƽΪʲôڼ
ǵĹף[Mehtre1][rao3]˵
ʿսӴָʶ𣬹ûüֱӳڷף
Ӧʿҵǰ[1]ʽ󣬳˹Ⳮ⣬Ҳ
ųǴģԭĲҲʲôԭڿ
רҾûֹʽĳϮʹ󣬵Ҳǡѧͨ
ѧо뷢չģʽʶ˹ܡڿˣ
ҲΪʲôйڿרҵˮƽΪʲôôãǰ
[1]ٺ5ƪϵĹأ[1]ο׶ûгѧ
оҪм̳ԣԺ󷢱¶ûƪ£Ҳ
ֳϮ¼ˣ[1]ֻ[lin 3]һС֣[lin 3]ʣ
ƵʹơӲ˲ǿݣ˶ʿʱΪá

˳ϮԡӢһͶ־һ⣬
ף[14]ƪ£ɽѧһƪһߵ£ڶ
ѧԺԺǰоָʶԺ
ԺùϵҲע⣬쵽ԺλҲףҪһ
ʱ̰Сˣˮ [12]ƪȫĲʿ
ģվأĵp27-34һȴϾѧŮ˶ʿ
ҵա[18] ƪ£ǰݵظһ̷
÷͵ǼʡùɲѧԺҲǹĹ
ȻѧĿ£ĻĿ˸ùϵ

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ȻųյĲʿˣҳϣѧõ˸
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ϴǮһһɽѧ˹ܽڡȻ־
Щͨѧ٣Ƶĺ޴µ£ռݱѧ
ҪλãŪ⻷ԼͷϣԼһרң
оʽԴͻЩб̤ʵѧʡ±Ƚ
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ýǮЩ˰оǵ֣򲻳ɾͿܴѹ
ЩֶͨΡɹʾЧӦӰһǵ·
ȥʹѧӸܡɽѧΪУҪסʵꡢС
汾µ̤ʵУѺʦҪѧƭӣ

(XYS20091109)

˿(www.xys.org)(xys4.dxiong.com)(www.xysforum.org)(xys2.dropin.org)

ϺѧѧԺȫĳϮ

ߣXiao

ã

ҲˣǵҸոտƪĵʱǴһ
˴ģĳϮƽδѾĺͱϮģ
顣

£

Solid State Communications 146 (2008) 311C314
doi:10.1016/j.ssc.2008.03.008  

һͨWei XuΪϺѧѧԺʿоά
http://www.gpxygpfx.com/qikan/manage/wenzhang/2008-02-0265.pdf
X.Y. JiangΪϺѧϿѧ빤ѧԺڽѩ
http://www.mat.shu.edu.cn/Default.aspx?tabid=2078&ctl=Detail&mid=2755&Id=13224&SkinSrc=[L]Skins/mat_con1/mat_con1
Z.L. ZhangΪϺѧʾӦüɽصʵҽ־
http://www.fpd.shu.edu.cn/Default.aspx?tabid=2970

˱޴ӿ

Ϯ£
Applied Physics Letters 90, 203512 2007
doi:10.1063/1.2741055

(XYS20091109)

˿(www.xys.org)(xys4.dxiong.com)(www.xysforum.org)(xys2.dropin.org)

ʷţڲQQԽڿ
ƾѧһݹʾְϽ

ƾѧ쵼

ĸУУʮʿʦ²ڿνţĴ
У걨ְƹʾʾڼ࣬ʵв
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УȺܶвʮʦɾ͡ջöɣ
ѧʿһҵϹоԺԺ(ѧУ
Ժ?)ھ͵вƵĲʿʦ(ǿǰشвƼ¼?)
Զ׼ȴŵóѣϹоԺվЩν
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ܡؼǹҽļѧУļִ½ʽĹ涨Ϊ


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[2]XYS, ־ԡϾѧѧƸ־ѧԡ
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(XYS20091109)

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ġǮѧɭ20ʴиСһĵ߼

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1.ѾΪ˱
2.ѾΪϢˣΪãⲻϢ㡱
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