Thuật Toán Adaboost Và Mạng Neural Trong Nhận Dạng Và Bám Đuổi Biển Số Xe

7/21/2019 Thut Ton Adaboost V Mng Neural Trong Nhn Dng V Bm ui Bin S Xe

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AI HOC QUC GIA THA NH PH H CHI MINHTR NG A I HOC BA CH KHOA

KHOA IN IN TB MN IU KHIN T NG

LUN VN TT NGHIP

THUT TON ADABOOST V MNG NEURAL

TRONG NHN DNGV BM UI BIN S XE

GVHD : KS. L NGC NH

SVTH : L C HNH

MSSV : 40700703

TP.H CHI MINH, 12/2011


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H QUC GIA TP. H CH MINHTRNG I HC BCH KHOA

----------

S: /BKT

KHOA: IN - IN TB MN: IU KHIN T NG

CNG HA X HI CH NGHA VIT NAMc lp - T do - Hnh phc.

----------

NHIM V LUN VN TT NGHIP

H V TN: L C HNH MSSV: 40700703

NGNH: IU KHIN T NG LP: DD07TD1

1.u lun vn:

THUT TON ADABOOST V MNG NEURAL TRONGNHN DNG V BM UI BIN S XE

2. Nhim v (Yu cu v ni dung v s liu ban u):........

3. Ngy giao nhim v lun vn:4. Ngy hon thnh nhim v: ...5. H v tn ngi hng dn: Phn hng dn

1. KS. L NGC NH ..2. .. .

Ni dung v yu cu LVTN c thng qua B Mn.Ngythngnm..

CH NHIM B MN NGI HNG DN CHNH(K v ghi r h tn) (K v ghi r h tn)

PHN DNH CHO KHOA, B MN:Ngi duyt (chm s b): .n v:.

Ngy bo v im tng kt..

Ni lu tr lun vn ...


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I HC QUC GIA TP.HCH MINH CNG HA XAHI CHNGHA VIT NAMTRNG I HC BCH KHOA C LPTDOHNH PHC

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

S: ______ /BKTKhoa: inin t

BMn: Tng

PHIU CHM BO VLVTN(Danh cho ngi hng dn)

1. Hv tn SV : MSSV : Ngnh (chuyn nganh) : .

2. ti : ...

3.

Htn ngi hng dn: .4. Tng quat vbn thuyt minh :

Strang : ............................................... Schng : ..Sbng sliu : .................................... Shnh v: ..Sti liu tham kho : .......................... Phn mm tnh toan :Hin vt (sn phm) : ............................

5. Tng quat vcc bn v:Sbn v: bn A1 bn A2 khkhcSbn vtay: Sbn vtrn may tnh :

6.

Nhng u im chnh ca LVTN:............................................................................................................................................................................................................................................................................................................................................................................................

7. Nhng thiu so t chnh ca LVTN:...........................................................................................................................................................................................................................................................................................................................................................................................

8.

ngh: c bo v Bsung thm bo v Khng c bo v9. Cu hi SV phi trli trc H i ng :a. ...................................................................................................................................................................................................................................................... .

b. ...................................................................................................................................................................................................................................................... .c. ...................................................................................................................................................................................................................................................... .

anh gia chung (bng ch: gii, kh, TB) : im _____/10K tn (ghi rohtn)


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I HC QUC GIA TP.HCH MINH CNG HA XAHI CHNGHA VIT NAMTRNG I HC BCH KHOA C LPTDOHNH PHC

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

S: ______ /BKT Ngy thang nmKhoa: inin t

BMn: Tng

PHIU CHM BO VLVTN(Danh cho ngi phn bin)

1. Hv tn SV : MSSV : Ngnh (chuyn nganh) : ..

2. ti : ..

3. Htn ngi phn bin:4. Tng quat vbn thuyt minh :

Strang : ............................................... Schng : ..Sbng sliu : .................................... Shnh v: ..Sti liu tham kho : .......................... Phn mm tnh toan :Hin vt (sn phm) : ............................

5. Tng quat vcc bn v:Sbn v: bn A1 bn A2 khkhc

Sbn vtay: Sbn vtrn may tnh:6. Nhng u im chnh ca LVTN:...

..............................................................................................................................

..............................................................................................................................

..............................................................................................................................7. Nhng thiu so t chnh ca LVTN:.

..............................................................................................................................

..............................................................................................................................

..............................................................................................................................

8.

ngh: c bo v Bsung thm bo v Khng c bo v9. Cu hi SV phi trli trc H i ng :a. .......................................................................................................................................................................................................................................................

b. .......................................................................................................................................................................................................................................................c. .......................................................................................................................................................................................................................................................

anh gia chung (bng ch: gii, kh, TB) : im _____/10K tn (ghi rohtn)


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i

Li Cm n

Trc ht con xin gi li cm n n gia nh, lun khch lv l chda tinh

thn cho con trong sut qu trnh hc tp va qua.

Knh gi n thy L Ngc nh li cm n chn thnh v su sc, cm n thy

tn tnh hng dn v a ra li khuyn em c thhon thnh lun vn tt nghip.

Em xin chn thnh cm n tt ccc thy c ca trng i Hc Bch Khoa

TP.HCM ni chung , qu thy c ca khoa inin Tv bmn iu Khin Tng ni ring tn tnh ging dy v trang bnhng kin thc cn thit cho em trong

sut thi gian hc tp ti trng.

V ti xin c cm n nhng ngi bn gip ti rt nhiu trong qu trnh

hc tp cng nhkhi thc hin lun vn ny.

Sau cng, em xin c gi li chc sc khe, hnh phc n qu thy c, gia nh

v bn b.

Tp.HCM, ngy 25 thng 12 nm 2011

L c Hnh


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ii

TM TT LUN VN

Ngy nay vi spht trin nhy vt ca Khoa hc kthut, con ngi to nnv pht trin nhiu cng trnh khoa hc mang tnh tm c. Vi sthay thdn ca my

mc cho con ngi trong cc nhim vmang tnh chnh xc v tp trung cao th kt qu

t c hon ton c tin cy v nh gi cao. iu ny thc sc ngha to ln

v gp phn tng thm gi trv cht lng cuc sng.

ti lun vn ny, nhn dng danh tnh xe v bm ui trn c sthgic my

tnh, cng khng nm ngoi ngha . y l mt hng nghin cu th vv nghav nhu cu thc tin v c nhiu phng php tip cn.

Hng gii quyt ti ca sinh vin l nhn dng danh tnh xe bng nhn dng

bin sxe. Vit Nam phng tin giao thng chyu l xe gn my nn trong lun vn

sinh vin chn bin sxe my, gm 2 hng v 8 k t. Bm ui xe da trn khong

cch tnh c gia 2 xe. Tt ccc gii thut, chng trnh nhn dng v tnh khong

cch u da trn c sthgic my tnh.

Cthnhng vn chnh c t ra v cn gii quyt ti ny l:

Tm hiu vngn nglp trnh C++, phn mm Microsoft Visual Studio 2008 v

th vin m ngun mOpenCV ca Intel.

Nghin cu c sl thuyt ca thut ton Adaboost vi c trng Haar-like p

dng cho nhn dng bin sxe thnh nh webcam thu v.

Tm hiu cc c trng ca mng neural v cc phng php hc cho mng, pdng cho bi ton nhn din k t.

To c sdliu lu bin sxe c thtng tc c.

Tnh khong cch n xe cn bm ui bng phng php hnh hc v phng

php Stereo Vision.

Tm hiu vi xl Pic 16F887, phn mm lp trnh CCS, phng thc truyn thng

RS232 nhn k ttmy tnh xung vi xl.

Xy dng hon chnh m hnh cn thit cho lun vn .


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iii

Mc Lc

Mc Trang

Trang ba

Nhim vlun vn

Phiu chm lun vn

Li cm n i

Tm tt lun vn ii

Mc lc iii

Danh sch hnh v vii

CHNG 1: GII THIU 1

1.1 Gii thiu 1

1.2 Mc tiu lun vn 1

1.3 M hnh ha hthng 2

1.4 Gii hn ti 3

1.5 ngha ca ti 3

CHNG 2: S LC VXL NH 4

2.1 Tng quan vmt hthng xl nh 4

2.2 Cc khi nim c bn trong xl nh 5

2.2.1 Phn tnh 5

2.2.2 nh 5

2.2.3 Mc xm 6

2.2.4 nh en trng 6

2.2.5 nh mu 7

2.2.6 Cc nh dng c bn 10

2.3 Cc vn c bn trong xl nh 11


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iv

2.3.1 Thit bthu nhn nh 11

2.3.2 Sha nh 11

2.3.3 Tin xl nh 122.3.4 Phn tch nh 13

2.3.5 c trng ca nh 13

2.4 Cc th vin m ngun mhtrcho xl nh 13

Chng 3: TH VIN XL NH OPENCV 14

3.1 Nhng chc nng ca OpenCV 14 3.2 Cu trc ca OpenCV 16

3.3 Mt shm thng dng ca OpenCV 17

3.3.1 Cc hm biu din nh 17

3.3.2 Cc hm xl v phn tch nh 18

3.3.3 Bin ca nh v cc hm xl 20

3.3.4 Xoay nh 22

3.3.5 Nhn din hnh chnht 25

Chng 4: THUT TON ADABOOST V HUN LUYN FILE NHN DNG 27

4.1 Phng php pht hin bin s 27

4.1.1 c trng Haar-Like 27

4.1.2 Thut ton tng tc Adaboost 30

4.1.3 Cascade of classtifier 34

4.2 Hun luyn file nhn dng 37

4.2.1 Gii thiu vbnhn dng 38

4.2.2 Thu thp v xy dng dliu hun luyn 38

4.2.3 Quy trnh hun luyn trn my tnh 40

Chng 5: MNG NEURAL NHN TO 49

5.1 Khi nim 49


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v

5.1.1 Neural nhn to 49

5.1.2 Mng neural nhn to 50

5.2 Phn loi mng neural nhn to 515.2.1 Mng dn tin 52

5.2.2 Mng quy hi 52

5.3 Hun luyn mng neural 53

5.3.1 Hc c gim st 54

5.3.2 Hc khng gim st 54

5.3.3 Hc tng cng 54

5.4 Mng perceptron v thut ton lan truyn ngc 55

5.4.1 Mng perceptron mt lp n 55

5.4.2 Mang perceptron nhiu lp 56

5.4.3 Thut ton lan truyn ngc ng dng trong mang MPL 56

5.5 ng dng ca mng neural trong nhn dng k tv sca bin sxe 59

CHNG 6: VI XL PIC 16F887 V GIAO TIP RS232 63

6.1 Tm hiu vi xl Pic 16F887 63

6.1.1 Gii thiu vvi xl Pic 16F887 63

6.1.2 S chn ca Pic 16F887 64

6.1.3 iu khin ng c bng PWM 69

6.2 Phn mm bin dch CCS 72

6.3 Giao tip RS232 74

6.3.1 u im ca giao tip ni tip RS232 74

6.3.2 Cng RS232 trn PC 74

6.3.3 Mch giao tip RS232 dng IC Max232 75

CHNG 7:THIT KV GII THUT 77

7.1 Thit kphn cng 77


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vi

7.1.1 Mch sdng iu khin xe 77

7.1.2 Ton cnh m hnh 82

7.2 Gii thut v lu 837.2.1 Gii thut tng qut 83

7.2.2 Gii thut xl nh 84

7.2.3 Gii thut iu khin robot 94

CHNG 8: KT QUT C V HNG PHT TRIN 95

8.1 Kt qut c 95

8.1.1 Kt quphn mm 95

8.1.2 Kt qum hnh 102

8.2 Thng k tl 102

8.3 Kt lun 105

8.4 Hn chca ti 105

8.5 Hng pht trin ca ti 106

Ti Liu Tham Kho 107

PhLc 108


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vii

Danh mc hnh nh

Hnh nh Trang

Hnh 1.1: M hnh ha hthng 2

Hnh 2.1: Cc giai on chnh trong xl nh 4

Hnh 2.2: nh tng tv nh s 6

Hnh 2.3: Di phin t(Electromagnetic Spectrum) 7

Hnh 2.4: Khng gian mu v cc mu c bn RGB 8

Hnh 2.5: Cc mu c bn ca hmu CMY 9

Hnh 2.6: Khng gian mu HSV 10

Hnh 2.7: S sha nh 12

Hnh 2.8: M tqut theo hng, ly mu theo hng v m ha tng hng 12

Hnh 3.1: Cu trc c bn ca th vin OpenCV 16

Hnh 3.2: Hm lc cvSmooth 18

Hnh 3.3: Hm truy nhp v chnh sa gi trim nh 20

Hnh 3.4: Phng php Canny vi ngng 100 v 500 21

Hnh 3.5: D bin houghline 22

Hnh 3.6: Xoay nh 1 gc anpha 22

Hnh 3.7: Minh ha thut ton xoay im 23

Hnh 3.8: Xoay nh theo phng pho reverse mapping 24

Hnh 3.9: Nhn din hnh chnht bng hm cvPolyLine 25

Hnh 3.10: Bin ssau khi c tch ring 26

Hnh 4.1a: 4 c trngHaar-like c bn 27

Hnh 4.1b: Cc c trng cnh 27

Hnh 4.1c: Cc c trng ng 28


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viii

Hnh 4.1d: Cc c trng bao quanh tm 28

Hnh 4.1e: c trng ng cho 28

Hnh 4.2: nh chia nhti ta (x,y) 29

Hnh 4.3: Tng cc gi trpixel nm trong vng A 29

Hnh 4.4: Lc c bn ca AdaBoost 30

Hnh 4.5: Thut ton hc AdaBoost 31

Hnh 4.6: Dng chui cascade pht hin ca scon ph hp 35

Hnh 4.7: Cu trc cc chui cascade song song 35

Hnh 4.8: Cu trc cc chui cascade ni tip 36

Hnh 4.9: Mt snh positive trong tp hun luyn 39

Hnh 4.10: Mt snh negative trong tp hun luyn 39

Hnh 4.11: Khoanh vng cha c trng ca i tng 1 41

Hnh 4.12: Khoanh vng cha c trng ca i tng 2 41

Hnh 4.13: To file vector.vec 43

Hnh 4.14: Qu trnh hun luyn file nhn dng 46

Hnh 4.15: Kt qunhn dng 48

Hnh 5.1: M hnh mt neural nhn to 49

Hnh 5.2: S n gin vmt mng neural nhn to 51

Hnh 5.3: Mng tin vi mt mc neural 52

Hnh 5.4: Mng tin kt ni y vi mt mc n v mt mc u ra 52

Hnh 5.5 : Mng hi quy khng c neural n, khng c vng lp t phn hi 52

Hnh 5.6: Mng hi quy c cc neural n 53

Hnh 5.7: Mng perceptron mt lp n 55

Hnh 5.8 Mng perceptron nhiu lp 56


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ix

Hnh 5.9: Lan truyn tn hiu trong qu trnh hc 57

Hnh 6.1: S chn VXL PIC16F887 64

Hnh 6.2: Chn reset 65

Hnh 6.3 Nhm chn to xung Clock 65

Hnh 6.4: Thanh ghi Trisa, Port A 66

Hnh 6.5: Cu trc chn t RB0 n RB3 v RB4 n RB7 67

Hnh 6.6: Thanh ghi TrisB v PortB 67

Hnh 6.7: Thanh ghi TrisC v Port C 68

Hnh 6.8: Thanh ghi TrisD v Port D 68

Hnh 6.9: Thanh ghi TrisE v PortE 69

Hnh 6.10: Chu k xung 71

Hnh 6.11: Khi to project trong phn mm CCS 73

Hnh 6.12: Cng com 9 chn 74

Hnh 6.13: Mch RS232 dng IC MAX232 76

Hnh 6.14: Cp chuyn i tUsb sang Com 76

Hnh 7.1: S nguyn l mch ngun 5VDC 77

Hnh 7.2: Mch ngun 5VDC 77

Hnh 7.3: S mch iu khin 78

Hnh 7.4: Mch iu khin PIC16F887 79

Hnh 7.5: Mch cng sut sau khi thi cng 79

Hnh 7.6: S mch cng sut 80

Hnh 7.7: Mch iu khin robot 81

Hnh 7.8: Phn khung robot 82

Hnh 7.9: M hnh robot hon chnh 82

Hnh 7.10: ng chy ca robot 83

Hnh 7.11: Qu trnh chia li k t 89

Hnh 7.12: Qu trnh nh xtma trn im sang ma trn gi tr 90

Hnh 7.13: M hnh ha thut ton c lng khong cch 91


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x

Hnh 7.14: S khi mt hthng stereo vision 93

Hnh 8.1: Giao din chng trnh iu khin 95

Hnh 8.2: Pht hin bin s 96

Hnh 8.3: Lc bin v tnh gc vi houghline 97

Hnh 8.4: Bin ssau khi xoay vhnh chnht 97

Hnh 8.5: Phn bin sc tch khng c nn 97

Hnh 8.6: Tch dng 1 98

Hnh 8.7: Tch dng 2 98

Hnh 8.8: Lu cc k tv strong khung kt qunhn din 99

Hnh 8.9: Kt qunhn din bng mng neural 100

Hnh 8.10: Tnh khong cch v bm ui theo bin s 101

Hnh 8.11: M hnh phn cng hon chnh 102

Hnh 8.12a: Mt shnh nh thnghim nhn dng vi nh sng trong nh 103

Hnh 8.12b: Mt shnh nh thnghim nhn dng vi nh sng ngoi tri 103


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Chng 1: Gii Thiu GVHD: Ks L Ngc nh

SVTH: L c Hnh - 40700703 Trang 1

CHNG 1:

GII THIU

1.1Gii thiu

Khoa hc kthut ca chng ta ngy cng pht trin, c nhiu thnh tu to ln v ng

dng thc tnhm nng cao cht lng cuc sng. Mt trong scc thnh tu chnh l

cng nghchto robot tng.

Robot c nhng tin br rt trong na thkqua. Tnhng nm 60 robot thay

thcon ngi lm vic trong cc mi trng c hi. Ngy nay do nhu cu sdng trong

mi trng sn xut phc tp nn robot cng nghip cn thch ng linh hot v thng

minh hn.Robot cn phi thy c v suy ngh c. chto c robot nh

vy yu tquan trng khng ththiu c chnh l ThGic My Tnh. ThGic

My Tnh gip robot c thnhn bit c mi trng xung quanh v tnh ton a ra

phng n thchhp nht.Pht hin v nhn dng i tng trong ThGic My Tnh l cng vic tm kim v ghi

nhn i tng trong nh hoc video. C nhiu thut ton gip robot c thnhn dng v

ni bt trong s l thut ton Adaboost, c thnhn dng mt ngi, k t, bn tay,

bin sxe mt cch nhanh chng v chnh xc.

Nhn thy y l mt hng pht trin nhiu tim nng v th vnn trong lun vn

sinh vin sdng ThGic My Tnh nhn din bin sxe, tnh ton khong cch

iu khin xe thnh bm ui theo mt xe khc trong phm vi cho trc. C thng

dng cho cc xe chhng ha tng bm nhau trong kho hng, trong nh my

1.2Mc tiu lun vn:

- Tm hiu vngn nglp trnh C++, phn mm Microsoft Visual Studio 2008 v

th vin m ngun mOpenCV ca Intel.


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- Nghin cu c sl thuyt ca thut ton Adaboost vi c trng Haar-like p

dng cho nhn dng bin sxe thnh nh webcam thu v.

- Tm hiu cc c trng ca mng neural v cc phng php hc cho mng p

dng cho bi ton nhn din k t.

- To c sdliu lu bin sxe c thtng tc c.

- Tnh khong cch n xe cn bm ui bng phng php hnh hc v phng

php Stereo Vision.

- Tm hiu vi xl Pic 16F887, phn mm lp trnh CCS, phng thc truyn thng

RS232 nhn k ttmy tnh xung vi xl.

-

Xy dng hon chnh m hnh cn thit cho lun vn ( khung xe, mch vn hnh,ng chy )

1.3

M hnh ha hthng:

hiu r hn vnhng vn cn gii quyt v xc nh phm vi ca ti, sinh vin

sm hnh ha hthng nh sau:

nh tc ng vo

Adaboost

Khng

C Mng

Neural

PP hnh hc RS232

PP Stereo vision

Hnh 1.1: M hnh ha hthng

Giao din iukhin (VC++)

Nhn dng ktv luvoc sdliu

Pht hinbin s

Tnh khongcch ti bins

iu khinng c theokhong cch


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1.4Gii hn ti:

- Vi thi gian khng nhiu v lng dliu hun luyn thu thp tng i sinh

vin cha nhn din c cc bin smu (xanh, ).

- Thut ton iu khin ng cchl ON OFF v ng c khng c encoder.

1.5 ngha ca ti :

- Gip tng ha qu trnh di chuyn ca cc xe chhng trong nh my, kho

hng.

- Qun l c cc phng tin di chuyn nhvo c sdliu c tng lu.


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Chng 2: S Lc VXL nh GVHD: Ks L Ngc nh


CHNG 2:

S LC VXL NH

2.1 TNG QUAN VMT HTHNG XL NH

Xl nh l mt ngnh khoa hc cn tng i mi mso vi cc ngnh khoa

hc khc, nht l trn quy m cng nghip, song trong xl nh bt u xut hin

nhng my tnh chuyn dng. hnh dung cu hnh mt my tnh chuyn dng, hay

mt hthng xl nh dng trong nghin cu, o to, trc ht chng ta sxem xt

cc bc cn thit trong xl nh.

Hnh 2.1 Cc giai on chnh trong xl nh

Qu trnh thu nhn nh:nh c ththu nhn qua camera. Thng nh thu nhn

qua camera l tnh hiu tng t(loi camera ng kiu CCIR) nhng cng c thl tnhiu sha (loi CCD-Charge Coupled Device). nh cng c ththu vtvtinh thng

qua cc bphn cm ng (sensor) hay nh c qut trn scanner.

Qu trnh sha (Digitalizer): nh sau khi thu vphi c sha, y l bc

kh quan trng chuyn i dliu tanalog sang digital thng qua ri rc ha (ly

mu) v sha bng lng tha. nh c sha xl, phn tch hay lu trbng

my tnh.


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Qu trnh xl s: bao gm cc cng on nh. Trc ht l cng vic tng

cng nh (Image Enhancement ) nng cao cht lng nh. Do nhng nguyn nhn

khc nhau: c thdo thit bthu nhn nh, do ngun sng hay do nhiu, nh c thsuy

bin. Do vy cn phi tng cng v khi phc nh (Image Restoration ) lm ni bt

mt sc tnh ca nh (Image Segmention), trch lc cc c tnh (Feature Extraction

)

Hquyt nh: Ty mc chca ng dng m chuyn sang giai on khc l

hin th, nhn dng, phn lp, truyn thng

2.2 CC KHI NIM C BN TRONG XL NH:

2.2.1 Phn tnh (pixel)

nh trong thc tl mt nh lin tc vkhng gian v vgi trsng. c

thxl nh bng my tnh cn thit phi tin hnh sha nh. Trong qu trnh sha,

ngi ta bin i tn hiu lin tc sang tn hiu ri rc thng qua qu trnh ly mu (ri

rc ha vkhng gian) v lng tha thnh phn gi tr(ri rc ha bin gi tr) m

vnguyn tc mt thng khng phn bit c hai im knhau. Trong qu trnh nyngi ta sdng khi nim pixel hay phn tnh. Nh vy nh l tp hp ca cc pixel.

Mi pixel gm mt cp ta m,n v mu sc. Mt pixel c thlu tr1, 4, 8 hay 24

bit.

2.2.2 nh

Tn hiu nh thuc loi tn hiu achiu: ta (x,y,z), sng(),thi gian(t).

nh tnhtrong khng gian 2 chiu c nh nghal mt hm 2 bin S(x,y), vi S

l gi trbin (c biu din bng mu sc) ti vtr khng gian (x,y).

Phn loi nh

+ nh tng tS(x,y): (x,y) lin tc, S lin tc.

+ nh sS(m,n): (m,n) ri rc, S ri rc.

Mt nh (gm mt tp cc im nh) c thxem nhbao gm tp cc nh con

(cc vng nh). Thut nggi l ROIsvng quan tm (Regions of Interest).


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nh strong khng gian ri rc thu c tnh tngttrong khng gian lin

tc thng qua qu trnh sha. Qu trnh sha c thhiu ngin nhsau:

+ nh tng tc chia thnhM hng,N ct.

+ Giao ca hng v ct c gi l: pixel

+ Gi trbin ca pixel ti ta nguyn (m,n) l s(m,n): l trung

bnh sng trong pixel . S(m,n)L (L smc xm dng biu din

nh).

M, N thng c chn lM=N=2K (K=8,9,10). L =2B ,B l sbt m ha cho

sng (bin ) mi pixel.nh sc biu din bi ma trn 2 chiu. Cc phn tca n l biu din

cho cc pixel sha.

Ta k hiu 1 nh sl S(M,N). Ta ni nh c phn giiMxN. K hius(m,n)

chra mt phn tnh.

Hnh 2.2nh tng tv nh s

2.2.3 Mc xm (gray level)

Mc xm l kt quca sm ha tng ng vi mt cng sng ca mi

im nh vi mt gi trs, kt quca qu trnh lng tha. Cch m ha kinh in

l dng 16, 32 hay 64 mc. M ha 256 mc c dng phbin. Do 28= 256 nn mi

pixel c m ha bi 8 bit.

2.2.4 nh en trng


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Thc tnh en trng gm c nh nhphn v nh a cp xm. Chng ta phn

bit sbin i thnh L mc. Nu L bng 2, ngha l chc hai mc 0 v 1 cn gi l

nh nhphn. Nu L ln hn hai mc ta c nh a cp xm. Vic xc nh smc ph

thuc vo tiu ch lng tha. L thng c chn bng 32, 64, 128 v 256. Trong

nh a cp xm 256 mc l nh c cht lng cao v thng c sdng.

Vi nh nhphn, mi pixel c m ha trn mt bit. Cn vi nh xm 256 mc

c m ha trn 1 byte = 8 bit. nh nhphn kh n gin, cc phn tnh c thcoi

nh phn tlogic. nh nhphn c dng theo tnh logic, phn bit nh vi nn

hay n gin phn bit bin vi im khc.

2.2.5 nh mu

Hnh 2.3 Di phin t(Electromagnetic Spectrum)

Mu sc ca mt tia sng l cm gic m tia sng gy nn mt ngi. Mu

sc ca vt thl mu ca nh sng pht tchng. nh sng ny nm trong di ph

nhn thy (visible).

Ty theo ngcnh nht nh m nh mu c din ttheo nhng m hnh mu

khc nhau. Khng c m hnh mu no l y cho mi kha cnh ca mu. Do


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ngi ta sdng nhng m hnh mu khc nhau m tcc tnh cht c nhn bit

khc nhau ca mu.

V d:

+ M hnh mu RGB: nh sng Red, Green, Blue ng dng cho mn hnh,

Ti Vi.

+ M hnh HSV: Nhn thc con ngi.

+ M hnh CYK: My in.

Chng ta i su vo mt sm hnh mu sau:

M hnh mu RGBTheo l thuyt mu do Thomas a ra tnm 1802, mi mu u c ththp t

ba mu c bn: (Red), Lc (Green), Lam (Blue). Ba mu ny l cc mu c bn ca

hmu cng (Additive Color System). Hmu RGB da trn c shthng ta

Cartesianhthng ta Decac: mi mu c bn u c m ha bi 8 bit, vy vi

ba mu phi hp nhau to thnh 2563= 16.777.216 mu thcp m mt ngi c th

cm nhn c. nh mu c lu trtng mu ring bit nh nh a cp xm. ng

vi mt pixel ca nh mu schim 3 byte, do nh mu schim bnhgp ba ln

nh a cp xm cng kch thc.

Hnh 2.4 Khng gian mu v cc mu c bn RGB

M hnh mu CMY:


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Gm ba mu c bn: Xanh L (Cyan), Tm (Magenta), Vng (Yellow), l b mu

ca khng gian mu RGB, cn gi l hmu tr(Subtractive Color System). Mi quan

hgia hai khng gian:

C = 1R

M = 1G

Y = 1B

Hnh 2.5 Cc mu c bn ca hmu CMY

M hnh mu HSV (Hue, Saturation, Value) :

Da trn cm nhn mu sc ca con ngi. nh sng mu l thp ca nh sng

n sc. Mt ngi chc thcm nhn c vi chc mu, song li c thphn bit ti

hng ngn mu. M hnh HSV suy din tm hnh RGB: hy quan st hnh hp RGB

theo ng cho tWhite n Black (gc)ta c hnh chp nn, sdng lm nh

hnh nn HSV.

C ba thuc tnh chyu trong cm nhn mu:

+ Hue: bc sng ca nh sng, c biu din bng gc t0o360ogip ta

phn bit cc mu khc nhau.

+ Saturation: bo ha, o tinh khit ca nh sng gc. S nm trong khong

[0-1].


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Hnh 2.6 Khng gian mu HSV

+ Value (brightness): cng hay chi nh sng. V c gi trtrong khong

[0-1], V = 0c mu en.

M hnh HSV trc gic hn m hnh RGB. Bt u tHue (H cho trc v V=1,

S=1). Thay i S: bsung hay bt trng; thay i V: bsung hay bt en n khic mu mong mun.

2.2.6Cc nh dng c bn

Qu trnh pht trin ca kthut xl nh tn ti nhiu nh dng khc nhau tnh en

trng IMG cho n nh a cp xm, nh mu: PCX, GIF, JPEG,

nh IMG:l nh en trng. Phn u ca nh IMG c 16 byte cha cc thng tin

cn thit ca nh. nh IMG c nn theo tng dng. Mi dng bao gm cc gi, cc

dng ging nhau cng c nn thnh cc gi. Ton bnh chgm c nhng im

sng v im ti l cc bit 0 hoc 1.

nh PCX:l mt trong nhng nh dng cin nht. N sdng lot m di

RLE nn dliu nh. Qu trnh nn v gii nn c thc hin trn tng dng nh.

Thc tphng php nn PCX km hiu quhn kiu IMG.


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nh GIF: c li vkhng gian lu tr, vi nh en trng kch thc tp c th

nhhn bn gc t5-7 ln; vi nh 16 mu, kch thc nhhn nh gc 2-3 ln, c

trng hp xp xnh gc. Tuy nhin vi nh 256 mu th n bc lkhnng nn rt

km.

nh JPEG:sdng chun nn cho nh tone lin tc. Tiu chun ny c thc

ng dng trong nhiu lnh vc: lu trnh, truyn b bo ch, nh y hc, camera s.

2.3 CC VN C BN TRONG XL NH

2.3.1 Thit bthu nhn nh

Cc thit bthu nhn nh thng thng gm: my quay (camera) cng vi bADC,

my qut (scanner) chuyn dng hoc cc bcm bin nh (Sensors). Hthng thu nhn

nh thc hin hai qu trnh:

+ Cm bin: bin i nng lng quang hc thnh nng lng in.

+ Tng hp nng lng in thnh nh in.

Trong xl nh bng my tnh ta khng thkhng ni n cc thit bmonitor

hin thnh. Monitor c nhiu loi khc nhau:

CGA: 640x320x16 mu

EGA: 640x350x16 mu

VGA: 640x480x16 mu

SVGA: 1024x768x256 mu

2.3.2 Sha nh

nh thu vtcc thit bthu nhn nh c thl nh tng thoc nh s. Trong

trng hp nh tng tchng ta phi tin hnh sha c thxl bng my tnh.

Phng php chung sha nh l ly mu theo hng v sha theo hng.


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Hnh 2.7 S sha nh

Hnh 2.8 M tqut theo hng, ly mu theo hng v m ha tng hng

2.3.3 Tin xl nh

Tin xl nh l qu trnh xl v nng cao cht lng nh. nh sau khi thu

nhn c nhiu thng tin khng quan trng, bnhiu, iu ny lm cho nh c dung

lng ln v c cht lng khng tt, gy kh khn cho vic phn tch nh sau ny.

Qu trnh tin xl nh chnh l qu trnh bin i nh, lm thay i ni dung ca

nh mt cch khng c bn nhng vn gic nhng thng tin quan trng ng thi

lm ni bt mt sc tnh quan trng ca nh.


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2.3.4 Phn tch nh

Phn tch nh l giai on tip theo ca tin xl nh. Qu trnh ny bin i nh

t a ra cc c trng quan trng ca nh. y l giai on quan trng nht ca

qu trnh xl nh. Trong phn tch nh, nh c tch ng bin hay phn on

thnh cc vng ring bit.

2.3.5 c trng ca nh

nh thu c sau khi thc hin cc qu trnh tin xl v phn tch nh sa ra

cc thng sca i tng cn quan tm trong nh. Tip theo cc thng sny sc

tnh ton li t a ra cc c trng ca i tng nh. y l giai on cui cng

ca mt qu trnh xl nh. Ty vo mc ch ng dng khc nhau m c thchn cc

c trng ph hp.

2.4 CC TH VIN M NGUN MHTRCHO XL NH

Chng ta c thsdng nhng thnh quca cng ng m ngun mp dng

cho ng dng xl nh ca mnh. Hin nay trn thgii c rt nhiu th vin m ngun

mcho chng ta sdng, cthl:

-Intel OpenCV (http://sourceforge.net/projects/opencvlibrary).

-CMVision (http://www.cs.cmu.edu/~coral/minnow/platform.html).

-ImLib 3D.

..

y sinh vin sdng th vin OpenCV ca hng Intel v tnh phbin v

khnng htrrt mnh trong vic xl nh ca th vin ny.
http://sourceforge.net/projects/opencvlibraryhttp://sourceforge.net/projects/opencvlibraryhttp://www.cs.cmu.edu/~coral/minnow/platform.htmlhttp://www.cs.cmu.edu/~coral/minnow/platform.htmlhttp://www.cs.cmu.edu/~coral/minnow/platform.htmlhttp://www.cs.cmu.edu/~coral/minnow/platform.htmlhttp://sourceforge.net/projects/opencvlibrary


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Chng 3: Th Vin XL nh OpenCV GVHD: Ks L Ngc nh


CHNG 3:

TH VIN XL NH OPENCV

OpenCV l mt th vin thgic my tnh m ngun mca hng Intel c thti

v t trang web http://SourceForge.net/Projects/opencvlibrary. Th vin c vit

bng C v C++. Intel a ra phin bn OpenCV u tin vo nm 1999. Ban u, n

chl th vin xl nh ca Intel. Vsau, tnh lthuc c loi bv by gi

ta c thsdng OpenCV nh mt th vin c lp. OpenCV l mt th vin a nn

tng, n chp nhn cWindow v Linux, hn thna gn y l Mac OSX. Mc tiu

ca OpenCV l cung cp c sc bn d s dng v thgic my tnh gip con

ngi c thto nn nhng ng dng xl nh phc tp mt cch nhanh chng.

Th vin OpenCV cha trn 50 chc nng ni nhp nhiu lnh vc trong x l

nh. N c nhiu tc dng nh: nhn dng mt, d tm mt, pht hin mt, lc Kalman,

n thhin sa dng ca tr tunhn to (AI). Thm vo n ci thin rt nhiu cc

thut ton cbn ca thgic my nh cc hm API cp thp hn. N c thl gim

st sn phm trong nh my, x l nh y khoa, an ninh, giao din ngi dng, lnh vc

robot

3.1NHNG CHC NNG CA OPENCV

- Image and Video I/O: Cc giao din ny cho php ta c c dliu nh tfile

hoc trc tip tvideo. Ta cng c thto cc file nh v video vi giao din ny.

- Thgic my ni chung v cc thut ton xl nh (General computer-vision

and image-processing algorithms (midand low level APIs)): Sdng nhng giao

din ny, ta c ththc hnh vi rt nhiu chun thgic my m khng cn phi c

m ngun ca chng. Chng bao gm sd tm vin, ng thng v gc, iu chnh

elip, ly mu v nhng bin i khc nhau (Fourier ri rc, cosin ri rc v cc bin

i khong cch,).
http://sourceforge.net/Projects/opencvlibraryhttp://sourceforge.net/Projects/opencvlibraryhttp://sourceforge.net/Projects/opencvlibrary


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- Modul thgic my cp cao: OpenCV gm mt vi tc dng cp cao.

Ngoi vic d tm, nhn dng v theo di khun mt, n cn bao gm clung thgic

(sdng camera di ng xc nh cu trc 3D), nh kch ccamera v m thanh

ni.

- AI and machine-learning: Cc ng dng ca thgic my thng yu cu my

mc phi hc ( machine learning) hoc cc hnh thc tr tunhn to khc (AI). Mt

vi trong schng l c sn trong gi OpenCV.

- Ly mu nh v php bin i:N thng rt tt cho qu trnh xl mt nhm

phn tnh nh l mt n v. OpenCV bao gm ly tch ra, ly mu ngu nhin,

phc ch, xoay nh, lm cong nh (warping), thay i hiu ng ca nh.- Cch thc to v phn tch nh nhphn:nh nhphn thng xuyn c

dng trong cc hthng kim tra c khuyt im hnh dng hoc cc bphn quan

trng. Sbiu din nh cng rt thun tin khi chng ta bit r vt thcn bt.

- Cch thc cho tnh ton thng tin 3D (methods for computing 3D

information):Nhng hm ny rt c ch khi cn sp xp v xc nh vi mt khi lp

th(with a stereo rig) hoc vi khng gian nhn phc tp (multiple views) tmt

camera ring.

- Cc php ton cho xl nh, thgic my v biu din nh (image

interpretation):OpenCV sdng cc php ton phbin nh: i stuyn tnh,

thng k v tnh ton hnh hc.

- ha:Nhng giao din ny gip ta vit chv vtrn hnh nh. Thm vo

nhng chc nng ny c sdng nhiu trong ghi nhn v nh du. V dnu bn

vit mt chng trnh cn nhn dng nhiu i tng th n srt c ch cho to nhn

nh (label image) vi kch thc v vtr.

- Phng thc GUI:OpenCV bao gm ca s giao din ca chnh bn thn n.

Trong khi nhng giao din ny c so snh gii hn vi khnng c ththc hin

trong mi mi trng. Chng cung cp nhng mi trng API a phng tin v n

gin hin thhnh nh, cho php ngi dng nhp dliu thng qua chut, bn

phm v iu khin qu trnh.


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- Cu trc dliu v gii thut:Vi nhng giao din ny bn c thgili, tm

kim, lu vo cch danh mc iu khin, cc tuyn tp (cng nh cc tp hp lnh

c gi), ha v s nhnh mt cch hiu qu.

- Khnng tn ti lu di ca dliu (Data persistence):Nhng phng php

ny cung cp cc giao din mt cch thun li lu trcc dng khc nhau ca d

liu vo a c thkhi phc khi cn thit.

3.2CU TRC CA OPENCV:

Cu trc ca OpenCV bao gm nhiu module:

Hnh 3.1 Cu trc c bn ca th vin OpenCV

-

CXCOREbao gm cc dng dliu c bn r rng. V dcu trc dliu vnh,

im, hnh chnht c xc nh trong file cxtypes.h. CXCORE cha cc php ton

i stuyn tnh v thng k, cc hm lu trlu di (persistence fun) v ccli

thao tc. Mc d vy cc hm ha phc vcho vic vnh cng c lu trti

y.

- CVcha ng qu trnh xl nh v cc phng php nh gi s bkch thc

nh. Nhng hm tnh ton hnh hc cng c lu trti y.


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- CVAUXc m ttrong vn bn ca OpenCV nh l module c v chdng

th nghim. Tuy nhin, giao din n gin nht cho nhn dng mt c nm trong

module ny. Nhng m ngun nm trong module ny rt ph hp cho vic nhn dng

mt v chng c sdng rng ri cho mc chny.

- Nhng hm cn li c nm trong HighGUIv CVCAM. Chai u nm th

mc c tn otherlibs, sdng chng rt dgp li. V rng HighGUI cha cc th

vin vo ra c bn , nn chc n hn, ta khng nn bst n. CVCAM l th vin

cha cc hm truy nhp video thng qua DirectX trn mi trng Window 32 bit.

HighGUI cng c cc giao din video, cha ng nhiu ca sa chc nng, lm vic

c trn nhiu mi trng v c bit hc OpenCV sn gin hn khi dngHighGUI.

3.3MT SHM THNG DNG CA OPENCV

3.3.1 Cc hm biu din nh:

Ly nh tcamera:

void CvCapture* cvCaptureFromCAM( int index );

Ly nh tvideo:

void CvCapture* cvCaptureFromFile( const char* filename );

Ly nh tmt file nh:

IplImage* cvLoadImage ( constchar* filename, intiscolor = CVLOADIMAGE

COLOR );

To ca shin thnh:

void cvNamedWindow ( const char*name, int flag=CV_WINDOW_AUTOSIZE );

Hm ny to ra mt ca svi tn name hin th nh. Khi

flag=CV_WINDOW_AUTOSIZE, hm sto ra ca sbng vi kch thc ca nh

v ngi sdng khng thnh li kch thc ca ca s. Nu flag=0, ngi sdng

c thnh li kch thc ca ca s.

Hin thnh:

void cvShowImage(const char* name, const CvArr* image);


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Hm ny dng xut nh image ra ca sngi dng c xc nh bi tn ca s

name. Hm ny chc sdng trong mi trng htrgiao din KDE.

Xa cu trc ly nh tcamera hoc video:

void cvReleaseCapture( CvCapture** capture );

3.3.2 Cc hm xl v phn tch nh:

Hm lc nh:

a. void cvSmooth(const CvArr* src,CvArr* dst,int smoothtype=CV;

GAUSSIAN,int param1=3,int param2=0,double param3=0,double param4=0 );

-

src: nh ngun ;- dst: nh ch ;

- smoothtype: phng php lm mt nh (CV_GAUSSIAN, CV_MEDIAN,

CV_BLUR_NO_SCALE, CV_BLUR).

Lm mt nh khnhiu, lm ni ln cc c tnh ca nh.

Hnh 3.2: Hm lc cvSmooth

b. void cvMorphologyEx(const CvArr* src, CvArr* dst, CvArr* temp,

IplConvKernel* element, int operation, int iterations=1)

- src: nh ngun ;

- dst: nh ch ;

Ton tmorphology v cc php ton ca n gip loi bnhiu vi nhng nh c

kch thc ln m nhng phng php khc lm vic khng hiu qu

Hm morphology sdng trong lun vn:


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cvMorphologyEx(Anh_Loc_Nhieu_Median,Anhxuly,NULL,NULL,CV_MOP_CLOS

E,1);

Hm chuyn i mu:

void cvCvtColor( const CvArr* src, CvArr* dst, int code );

- src: nh ngun 8 bit, 16 bit hay 32 bit;

- dst: nh ch c cng dliu nh nh ngun nhng c thkhc sknh mu;

- code: hmu cn chuyn i (CV_RGB2HSV, CV_RGB2GRAY,).

Hm ny c tc dng chuyn i hmu ca nh gc sang hmu khc hoc sang nhxm.

Hm truy nhp gi trmu ca im nh:

CvScalar cvGet2D( const CvArr* arr, int row, int col );

- arr: con trcha dliu ( CvArr*), dliu c thl hnh nh c cu trc

IplImage;

-

row, col: ta ca im nh cn truy cp.

Hm cvGet2D() trvcu trc cha thng tin mu sc dng C l CvScalar c xc

nh nh sau:

typedef struct CvScalar

{

double val[4];

}

CvScalar;

Gi trca mi im nh cho mi knh c nm trong val[i]. Vi nh en trng,

val[0] cha sng ca im nh. Ba gi trkhc c t gi tr0.

Vi nh BGR th blue = val[0], green = val[1] v red = val[2].

Hm chnh sa gi trim nh:

void cvSet2D(CvArr*, int row, int col,CvScalar);


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- arr: con trcha dliu ( CvArr*), dliu c thl hnh nh c cu trc

IplImage;

- row, col: ta ca im nh;

2 hm trn cvGet2D v cvSet2D p dng khi xc nh c ta ca bin strn

khung hnh bng phng php Adaboost(phn bao bi vin ) v ct ly khung hnh

cha bin s. Phc vcho cc thao tc chnh sa tip .

Hnh 3.3: Hm truy nhp v chnh sa gi trim nh

-

CvScalar: gi trmu sc.

Hm ny cho php ta gn gi trmu cho im nh ang xt ti ta (row, col).

3.3.3

Bin ca nh v cc hm xl:

Hm tch sn nh theo Canny

void cvCanny(const CvArr* image, CvArr* edges, double threshold1, double

threshold2, int aperture_size=3)

- image: nh ng vo

- edges: nh ng ra

- threshold1: ngng u tin

- threshold2: ngng th2


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Phng php Canny rt hiu quvi nh trong iu kin thng thng vsng

v tng phn. Tuy nhin vbn cht phng php ny da trn nguyn tc

o hm nn bin nhn c khng phi lc no cng n nh.

y l mt phng php c hiu qucao vi nh c nhiu.

Hnh 3.4:Phng php Canny vi ngng 100 v 500

Hm d bin HoughLine

CvSeq* cvHoughLines2(CvArr* image,void* line_storage,int method,double

rho,double theta,int threshold,double param1 = 0,double param2 = 0);

- image: nh ng vo

- line_storage: con trn mng nh

-

method: cc thut ton houghline nh CV_HOUGH_STANDARD,

CV_HOUGH_PROBABILISTIC, hay CV_HOUGH_MULTI_SCALE

- rho,theta: phn gii mong mun cho cc ng

- threshold: ngng mong mun

Thut ton HoughLine dng pht hin ra cc ng thng trong nh, p dng

trong lun vn sinh vin dng cc ng thng ny tnh gc lch ca bin s.


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Hnh 3.5: D bin houghline

on code sdng trong lun vn d bin theo phng php houghline

lines = cvHoughLines2( dst, storage, CV_HOUGH_PROBABILISTIC, 1,

CV_PI/180, 50, 50, 10 );

doublex2,y2;

for( i = 0; i < lines->total; i++ )

{CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);

cvLine( color_dst, line[0], line[1], CV_RGB(255,0,0), 3, CV_AA, 0 );

if(i==0)

{y2=(line[0].y-line[1].y);

x2=(line[1].x-line[0].x);

ALPHA = atan2(y2,x2);

}

}

3.3.4 Xoay nh

Hnh 3.6: Xoay nh 1 gc anpha

Thut ton sdng l quay tt ccc im quanh im trn cng bn tri ca nh mt

gc alpha theo chiu dng qui c. Gc alpha xc nh c nhtnh gc lch gia


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bin nh v bin ca bin s( dng phng php houghline ). C hai cch thc hin

vic xoay ny l nh xxui (forward mapping) v nh xngc (reverse

mapping).Forward mapping slm cho nh c l. Vi reverse mapping, nh mt hn

nhng cc mp vn khng c mm lm.

Forward mapping

Trongforward mapping, t mi im ca nh gc, xc nh mt im ca nh kt qu.

Do phi lm trn s khi thc hin php xoay nn nh gc, c nhng pixel khng

c "t mu" lm cho trn nh xut hin nhng "l" li ti.

Hnh 3.7: Minh ha thut ton xoay im

Cng thc

|x'| |cos(a) -sin(a)| |x|

| | = | | | |

|y'| |sin(a) cos(a)| |y|

Reverse mapping

Vireverse mapping, t mi im ca nh kt qu, suy ngc li t nh gc ly

ra gi tr mu cn thit. Vi cch ny, tt c cc im trn nh kt qu u c

gn gi tr mu ca mt im tng ng (hay t nht cng l im ln cn ca im

) nh gc nn khng c hin tng "l" nh trn.

Ta tm ma trn xoay nh trong trng hp nynh sau:


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Ta c:

|x'| |cos(a) -sin(a)| |x|

| | = | | | |

|y'| |sin(a) cos(a)| |y|

Nn:

|x| |cos(a) -sin(a)|-1 |x'|

| | = | | | |

|y| |sin(a) cos(a)| |y'|

Do :

|x| |cos(a) sin(a)| |x'|| | = | | | |

|y| |-sin(a) cos(a)| |y'|

Trong lun vn sinh vin sdng phng php reverse mapping do cho kt qu

mn hn nhiu.

Hnh 3.8: Xoay nh theo phng pho reverse mapping

on code sdng trong lun vn xoay nh

// Rotate

for (int i = -120; i < img->width*2; i++)for (int j = 0; j < img->height*2; j++)

for (int k = 0; k < img->nChannels; k++) {

int jN = (int)(j*cos(ALPHA) - i*sin(ALPHA));

if ((iN > 0) && (jN > 0)


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&& (iN < img->width) && (jN < img->height))

resData[(j)*res->widthStep

+ (i+120)*res->nChannels + k] =

imgData[jN*img->widthStep

+ iN*img->nChannels + k];}

3.3.5 Nhn din hnh chnht

OpenCV cung cp mt shm chng ta c thvtrc tip trn nh nh to ng

thng, hnh vung, hnh trn hay ty thch.

Trong lun vn sinh vin sdng hm cvPolyLine() vng bin ca hnh ch

nht

void cvPolyLine(CvArr* img, CvPoint** pts, int* npts, int contours, int is_closed,

CvScalar color, int thickness=1, int lineType=8, int shift=0)

- img: a bc nh cn vvo

- pts: L mt mng kiu cvPoint nn cng mt ln gi ta c thvc nhiu a

gic.

- npts: L mt mng dng cha snh ca cc a gic c v. Cng mt ln v

ta c thvc nhiu a gic c snh khc nhau.

- is_closed: Nu n bng true th sthm mt on ni im u vi im cui li

vi nhau.

- contours: Sng vin quanh a gic

Hnh 3.9: Nhn din hnh chnht bng hm cvPolyLine


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Sau khi tnh c ta ca 4 nh hnh chnht (c bao bi vin ) v ct

phn nh ring ra sc phn bin sdng chun.

Hnh 3.10: Bin ssau khi c tch ring

Sau sinh vin stch tng k t, sv nhn dng bng mng neural. Chi tit s

c trnh by cc chng sau.


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Chng 4: Thut Ton Adaboost GVHD: Ks L Ngc nh


CHNG 4

THUT TON ADABOOST V HUN LUYN

FILE NHN DNG

4.1 Phng php pht hin bin s

thc hin chc nng pht hin v nhn dng bin s, sinh vin trin khai s

dng thut ton pht hin i tng (da trn cc c trng Haar-like v thut ton tngtc AdaBoost) trn tng frame nh thu c tngun tn hiu hnh nh camera ri da

vo cc thut ton xl nh v thgic my tnh thi hnh cc tc vln cc bin sxe

c pht hin v nhn dng. Sau y l phn trnh by phng thc hot ng ca

phng php pht hin bin sxe bng cc c trng c lit k sau y:

4.1.1 c trng Haar-like

Do Viola v Jones cng b, gm 4 c trng c bn xc nh khun mt ngi.

Mi c trng Haarlike l s kt hp ca hai hay ba hnh chnht "trng" hay "en"

nh trong hnh sau:

Hnh 4.1a: 4 c trngHaar-like c bn

Hnh 4.1b: Cc c trng cnh


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Hnh 4.1c: Cc c trng ng

Hnh 4.1d: Cc c trng bao quanh tm

Hnh 4.1e: c trng ng cho

Gi trca c trng Haar-like c xc nh bi chnh lch gia tng cc gi

trpixel mc xm nm trong vng en so vi vng trng.

f(x) = Tngvng en(cc mc xm ca pixel) - Tngvng trng(cc mc xm ca pixel)

Sdng gi trny, so snh vi cc gi trca cc gi trpixel th, cc c trng Haar-

like c thtng/gim sthay i in-class/out-of-class (bn trong hay bn ngoi lp bin

sxe), do slm cho bphn loi dhn.

Cch dng nh chia nh (integral image) gip tnh ton nhanh chng cc c

trng Haar-like.


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Hnh chia nhvtr (x,y) bng tng cc gi trpixel pha bn tri ca ta (x,y)

bao gm:

yyxx yxiyxP ',' )','(),( (4.1)

Hnh 4.2:nh chia nhti ta (x,y)

Tng cc gi trpixel trong vng A:

P1= A1; P2= A2 ; P3= A1+ A3

P = A + A1+ A2+ A3 ; (4.2)

A = P + P1P2P3 ;

Hnh 4.3: Tng cc gi trpixel nm trong vng A

Tip theo, chn cc c trng Haar-like dng cho vic thit lp ngng, Viola v

Jones sdng mt phng php my hc c gi l AdaBoost. AdaBoost s kt hp

cc bphn loi yu to thnh mt bphn loi mnh. Vi bphn loi yu chcho ra


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cu trli chnh xc chhn vin on mt cch ngn nhin mt cht, cn bphn loi

mnh c tha ra cu trli chnh xc trn 60%.

4.1.2 Thut ton tng tc AdaBoost

AdaBoost (Adaptive Boost) l mt thut ton hc mnh, gip y nhanh vic to

ra mt bphn loi mnh (strong classifier) bng cch chn cc c trng tt trong mt

hcc bphn loi yu (weak classifier - bphn loi yu) v kt hp chng li tuyn

tnh bng cch sdng cc trng s. iu ny tht sci thin dn chnh xc nhp

dng hiu qumt chui cc bphn loi yu.

AdaBoost

Tp hun luyn

H cc bphn lp yu

B phnlp mnh

Cc trng s

Hnh 4.4: Lc c bn ca AdaBoost

Thut ton hc ny ban u duy tr mt phn b chun (tng ng nhau) cc

trng s ln mi mt mu hun luyn. Trong bc lp u tin, thut ton hun luyn

mt bphn loi yu bng cch dng mt c trng Haar-like thc hin tt nht vic

pht hin cc mu th hun luyn. Trong ln lp th hai, cc mu th dng cho hun

luyn nhng bphn loi nhm bi bphn loi yu u tin c nhn trng scao hnsao cho c trng Haar-like c chn ln ny phi tp trung khnng tnh ton cho cc

mu thbphn loi nhm ny. Slp li tip tc thc hin v cc kt qucui cng s

l mt chui cascade cc kt hp tuyn tnh ca cc bphn loi yu, to ra mt bphn

loi mnh, gip to c chnh xc mong mun. Thut ton hc AdaBoost sau 3 ln

lp c minh ha di yl mt v dthut ton AdaBoost sau ba ln lp.


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Hnh 4.5: Thut ton hc AdaBoost

L mt ci tin ca tip cn Boosting, AdaBoost sdng thm khi nim trng s

(weight) nh du cc mu nhn dng. Trong qu trnh hun luyn, cmi bphn

loi yu c xy dng, thut ton stin hnh cp nht li trng schun bcho

vic xy dng b phn loi yu k tip thng qua vic tng trng s ca cc mu b

nhn dng sai v gim trng sca cc mu c nhn dng ng bi bphn loi yu

va xy dng. Bng cch ny, cc bphn loi yu sau c th tp trung vo cc mu

m cc bphn loi yu trc n cha lm tt. Sau cng, cc bphn loi yu sc

kt hp tutheo mc tt ca chng to dng nn bphn loi mnh.

C th hnh dung mt cch trc quan nh sau: bit mt nh c phi l mt

ngi khng, ta hi T ngi (tng ng vi T bphn loi yu xy dng tT vng

lp ca tng cng), nh gi ca mi ngi (tng ng vi mt bphn loi yu)


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ch cn tt hn ngu nhin mt cht (t lsai di 50%). Sau , ta snh trng s

cho nh gi ca tng ngi (thhin qua hs), ngi no c khnng nh gi tt

cc mu kh th mc quan trng ca ngi trong kt lun cui cng scao hn

nhng ngi chnh gi tt cc mu d. Vic cp nht li trng sca cc mu sau

mi vng tng cng chnh l nh gi kh ca cc mu (mu cng c nhiu

ngi nh gi sai l mu cng kh).

Thut ton Adaboost:

1. Cho mt tp gm n mu c nh du (x1,y1), (x2,y2), (xn,yn) vi xk(xk1, xk2, , xkm) l vector c trng v yk(-1, 1) l nhn ca mu (1 ng vi object, -1 ngvi background).

2. Khi to trng s ban u cho tt c cc mu: vi m l s mu ng (ng vi

objectv y = 1) v ll s mu sai (ng vi background v y = -1).

1, = 1

2

,1

2

3. Xy dng T weak classifiers

Lp t = 1, , T

Vi mi c trng trong vector c trng, xy dng mt weak classifier hj

vi ngng j v li j.

=

,

|

|

Chn ra hjvi jnh nht, ta c ht:

: {1,1} Cp nht li trng s:

+1, = ,

, =

,


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Trong :

= 12ln (

1

)

: H s dng a +1v on [0,1] (normalization factor)4. Strong classifier c xy dng :

= ()

=1

Gii thch:

Qu trnh hun luyn bphn loi c thc hin bng mt vng lp m mi

bc lp, thut ton s chn ra bphn loi yu ht thc hin vic phn loi vi li t

nhnht (do sl bphn loi tt nht) bsung vo bphn loi mnh. Mi khi

chn c 1 bphn loi ht, AdaBoost stnh gi trttheo cng thc trn, tcng

c chn trn nguyn tc lm gim gi trli t.

Hstni ln mc quan trng ca ht:

- Trong cng thc phn loi H(x):

= ()

=1

Ta thy tt ccc bphn loi htu c ng gp vo kt quphn loi ca H(x),

v mc ng gp ca chng ph thuc vo gi trt tng ng: htvi tcng ln

th n cng c vai tr quan trng H(x).

- Trong cng thc tnh t:

= 12ln (

1 )


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Cc ca scon l tch cc (ph hp, d ng i tng) nu c cho qua ti tng

bphn lp ca chui cascade c hun luyn. Nu khng, mt ng ra trn chui s

loi bt k ca skhng ph hp ngay lp tc.

Hnh 4.6: Dng chui cascade pht hin ca scon ph hp

Bng cch s dng cu trc gm cc chui cascade song song, tc pht hin

i tng sc ci thin ng k.

Hnh 4.7: Cu trc cc chui cascade song song


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4.1.3.1 Giai on hun luyn ca bphn loi (stage)

Thut ton tng tc thch nghi c sdng lm phng php chnh pht hin

v pht hin i tng bin sxe trong lun vn. Thut ton tng tc l m hnh hc myhiu quc sdng nhiu trong cc ti vnhn dng trc y. M hnh ny chs

dng cc bphn loi yu.

Tc v hc c da trn N mu hun luyn NN yxyx ,,...,, 11 vikx v

1,1iy . ix v vect c thnh tk. Mi thnh tk c chc nng m ha mt c trng

c lin quan cho tc vhc. Ng ra mong mun sau khi m ha c hai gi trl -1 v 1.

Trong trng hp pht hin i tng vt th, thnh tng vo ix l mt c trng Haar-

like. Cc gi trng ra -1 v 1 cho bit nh xl c cha hay l khng cha i tng

mong mun.

4.1.3.2 Tng phn loi (cascade)

Tng (t) ca bphn loi bao gm cc cy (tree) gi trgim dn sau mi giaion (stage) m bphn loi c hun luyn nhn dng hu ht cc i tng vt th

mong mun, ng thi cng loi bcc i tng khng c hun luyn. V d, trong

lun vn ny, cc bphn loi c hun luyn qua t nht 20 giai on (stage). n giai

on cui cng, gi tr false alarm = 076.95.0 20 e v trng kht (hit rate) khong

9047.0995.0 20 .

h h h h h

. . . . .

1 - f 1 - f 1 - f 1 - f

hit-rate = hN

false-alarms = fN

stage 1 stage 2 stage 3 stage N

Hnh 4.8: Cu trc cc chui cascade ni tip, vi N giai on hc hun luyn


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Gis, thit lp ban u vi cc gi tr

995.0

5.0

ratehit

alarmfalse

Stage 1:

995.05.0

1

1

hf

Stage 2:

2

2

2

2

995.0

5.0

h

f

Stage 3:

3

3

3

3

995.0

5.0

h

f

Stage N:

N

N

N

N

h

f

995.0

5.0

Ti mi giai on hun luyn stage, b phn loi to ra thng s hit-rate h v

false-alarm ratef mi lm ng vo thng st cho giai on hun luyn ktip sau.

ng vi mi giai on c hun luyn sdng mt trong phng php tng tc.

Btng tc c thhc hun luyn bi mt mt phn loi mnh da trn mt tp hp cc

bphn loi yu bng cch d li trng scc mu hun luyn. Bphn loi yu c

dng cho giai on u ca qu trnh hun luyn, dng tp hp v c kt cc c

trng s ca tp hun luyn. Ti mi tng hun luyn, b phn loi da theo cc i

lng c trng va c cp nht ti tng k trc (false-alarm, hit-rate) c thm

vo nhm tng thm tnh chnh xc trong qu trnh tnh ton trng sc trng. Vi vic

tng dn sgiai on hun luyn v slng cc bphn loi yu, sl cn thit tnh

ra cc thng sfalse-alarm rateng vi mi hit-rate tnh c slm tng tnh chnh

xc cho tc vpht hin i tng.

4.2 Hun luyn file nhn dng


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Hnh 4.9: Mt snh positive trong tp hun luyn

Hnh 4.10: Mt snh negative trong tp hun luyn


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- maxzangle

Gc xoay ti a, tnh theo radian

-show

Nu c khai bo, mi mu to thnh s c hin ln. Nhn Escs tip tc

qu trnh to mu khng km theo hin hnh mu.

- w

Chiu rng tnh bng pixel ca kch thc hun luyn mu positive.

- h

Chiu cao tnh bng pixel ca kch thc hun luyn mu positive.

Hnh 4.13: To file vector.vec

i vi cc hnh khng tch cc ta cn to mt file cha danh sch tn cc nh.

Trong haarkit ch cn nhp i chut vo file c sn create_list.bat s t ng lu

danh sch ta cn trong file infofile.txt.


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4.2.3.3 Chy chng trnh hun luyn

Sau khi to xong cc mu hun luyn, ta tin hnh hun luyn dng chng trnh

haartraining.exec cc tham s nh sau:

- data

Tn ng dn n tp tin cha kt qu hun luyn

- vec

Tn file cha cc mu positive ( c to trc bi createsamples.exe)

- bg

File m t background

- npos ,

- nneg

S lng nh positive hay negative dng trong hun luyn.

- nstages

S lng stage mun hun luyn

- mem

Kch thc b nh dnh cho tnh ton hun luyn (n v MB). Dnh nhiub nh s gip tng tc qu trnhhun luyn.

- sym (mc nh),

- nonsym

Cho bit vt th trong hun luyn c i xng theo trc ng hay khng.


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Hnh 4.14: Qu trnh hun luyn file nhn dng

Sau khi chy xong chng trnh ny s to ra cc file cascade. Sau dng chng trnh

haarconv.exe s ghp cc cascade thnh 1 file c ui .xml. File ny c th dng

nhndngbin sxe.

on code sdng file nhn dng trong lun vn


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{cvFlip(currentFrame, tempFrame, 0);

}

// Perform face detection on the temporary image, adding a

rectangle// around the detected face.

faceDetection(tempFrame, facesMemStorage, classifier);

// Show the result in the window.

show = chiaanh(tempFrame);

cvShowImage("Result",show);

cvSaveImage("abc.jpg",tempFrame);

cvReleaseImage(&show);

// If a key is pressed, break out of the loop.

if(cvWaitKey(10) >= 0){

break;

}

if(vong >= 50)

{ vong=0;

break;

}}

Kt Qu:Tc nhn din ca phng php Adaboost rt nhanh, khong 20 ms cho

mt khung hnh c i tng.

Hnh 4.15: Kt qunhn dng


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Chng 5: Mng Neural Nhn To GVHD: Ks L Ngc nh


Hm kch hot hay cn gi hm kch hot phi tuyn, chuyn i mt t hp tuyn

tnh ca tt c cc tn hiu u vo thnh tn hiu u ra. Hm kch hot ny m bo tnh

cht phi tuyn cho tnh ton mng neural. N c xem nh l mt hm gii hn, n gii

hn phm vi bin cho php ca tn hiu u ra trong mt khong gi tr hu hn. M

hnh neural trong hnh 5.1 cn bao gm mt h s iu chnh b tc ng t bn ngoi. H

s iu chnh b c tc dng tng ln hoc gim i u vo thc ca hm kch hot, ty

theo n dng hay m.

5.1.2 Mng neural nhn to.

L mt h thng bao gm nhiu phn t x l n gin (hay cn gi l neural) ta

nh neural thn kinh ca no ngi, hot ng song song v c ni vi nhau bi cc

lin kt neural. Mi lin kt km theo mt trng s no , c trng cho tnh kch hot

hoc c ch gia cc neural.

C th xem cc trng s l phng tin lu tr thng tin di hn trong mng

neural v nhim v ca qu trnh hun luyn ca mng l cp nht cc trng s khi c

thm thng tin v mu hc. Hay ni mt cch khc, cc trng s u c iu chnh sao

cho dng iu vo ra ca mng s m phng hon ton ph hp vi mi trng ang xem

xt.

M hnh mng neural.

M hnh mng neural di gm 3 lp: lp nhp (input), lp n(hidden) v lp

xut (output). Mi nt trong lp nhp nhn gi tr ca mt bin c lp v chuyn vo

mng.


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5.4 Mng perceptron v thut tonlan truyn ngc.

5.4.1

Mng Perceptron mt lp n

Cu trc: mng Perceptron mt lp n c trng cho loi mng truyn thng c m t

trong hnh vdi y:

Hnh 5.7: Mng perceptron mt lp n

u vo ca mng c thc m tl vector X=[x1, x2,,xm]T, trong m l slng

u vo.

Gi trngng ca cc nron l cc trng lin kt vi u vo cui cng xm=-1. Vi n

nron, vector u ra thc tl Y=[y1,y2,,yn]. Mng Perceptron sdng lut hc c

gim st.

Do tng ng vi mu u vo l vector X(k)=[x1(k),x2(k),,xm(k)]T, mu u ra

mong mun l vector d(k)=[d1(k),d2(k),,dn(k)]T. Vi k=1, 2p; p l scp mu

vo/ra; ml su vo; nl su ra; T: l k hiu chuyn v.

Chng ta mun u ra thc sy(k)=d(k) sau qu trnh hc v c thc m tnh sau:

() = =( ()) = ()=1 vi i=1,2n; k=1,2p


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lp trong cc n-ron c th s dng cc hm chuyn l cc hm lin tc c cc dng

khc nhau.

Thut ton sdng mt tp cc mu gm cc cp u vo - u ra luyn mng. Vimi cp u vo - u ra (x(k),d(k)) thut ton lan truyn ngc sai sthc hin hai giai

on sau:

+Giai on thnht, mu u vo x(k)c truyn tlp vo ti lp ra, v ta c

kt quu ra tnh ton c l y(k)

+Giai on tip theo, tn hiu li c tnh ton tskhc nhau gia u ra

quan st c d(k)vi u ra tnh ton y(k)sc lan truyn ngc li tlp ra n cc

lp trc iu chnh cc trng sca mng. lm v dta xt mng truyn thng c

mt lp n di y, i vi cc mng c kch thc ln hn th thao tc cng tng t.

Mng n-ron c xt c m n-ron lp vo, l n-ron trong lp n v n n-ron lp ra.

ng klin thhin lung tn hiu c truyn tu vo ti u ra cn cc ng k

nt t thhin lung tn hiu li c truyn ngc trli tu ra.

Hnh 5.9: Lan truyn tn hiu trong qu trnh hc


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Qu trnh hun luyn l qu trnh hc vi cc tp mu cho vi tn hiu u vo Xjv tn

hiu u ra mong mun l Dj

1.

Khi to cc gi trban u, tc hc, sai sti a cho php Emax, gi trbanu ca cc trng skt hp lp vo v lp n Vqj v trng skt ni gia lp n

v lp ra Wiq . Chn k=1, E=0.

2. Lan truyn xui cc tn hiu u vo Xi qua mng cc phng trnh sau:

o Lp n:

=

vqj

xj

=1

= ()o

Lp ra:

==1 = ()o

Hm chi ph:

= 12()2

3. Cp nht trng s

o Sai sng ra ca lp ra:

=

= (1 )Vi i=1,2,no

Cp nht trng sgia lp n v lp ra + 1 =+ ()Vi q=1,2,l v i=1,2,n

o Sai sng ra ca lp n:


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= =1 = =1 (1)

o Cp nht trng sgia lp n v lp ra + 1 = + ()

Vi q=1,2,l v i=1,2,n

4. Nu k


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{delta1[i][j]=0.2*a[i]*dauraan[j];

//Cap nhat trong so lop ra moi

trongsolopra[i][j]= trongsolopra[i][j]+ delta1[i][j];

}}

Nu hm chi ph E


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Chng 6: Vi XL PIC16F887 V RS232 GVHD: Ks L Ngc nh


a)Nhm chn cp ngun:

Chn 11, 32: ni vo Vcc (+5V).

Chn 12, 31: ni mass.

b) Chn Reset (chn s1):

Vi iu khin PIC s c reset khi chn s 1 chuyn t mc logic 1

xung mc logic 0.

Hnh 6.2: Chn reset

c)Nhm chn to xung Clock:

Xung clock sc a vo chn s13 v 14, thch anh givi tr nh

tn cho mch dao ng bn trong chip. PIC 16F887 c thhot ng trong 4 ch

dao ng khc nhau.

Hnh 6.3: Nhm chn to xung Clock


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l chn nhp. Khi sdng Port C cn lu gi trca thanh ghi TRISC v mt schc

nng ngoi vi s lm cho cc chn Port C mc nh l Output. Trong khi , mt s

chc nng ngoi vi slm cho cc chn Port C l chn Input.

Vic c thanh ghi PortC sgip tra bit c trng thi chn ca PORTC. Vic

ghi gi trvo thanh ghi ny cng slm thay i trng thi logic cc chn ca Port C

Hnh 6.7: Thanh ghi TrisC v Port C

m.Port D v TRISD:

Port D c tm chn tRD0 n RD7. Port D c th hot ng nh l mt Port

xut nhp thng thng hoc nh mt cng song song ca PSP (Parallel Slave Port)

bng cch set bit PSP mode (TRISE.4) ln 1. Trong chny, buffer ng vo l linh

kin hTTL.

Hnh 6.8: Thanh ghi TrisD v Port D

n. Port E v TRISE:

Port E c nm chn, trong c ba chn RE0/RD/AN5, RE1/WR/AN6,

RE2/CS/AN7 c thc cu hnh l cc chn xut nhp.

Cc chn Port E c thtrthnh cc chn iu khin cho cc cng ca vi xl.


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Khi bit PSPMODE (TRISE.4) c set ln 1. Khi , cc bit t 0 n 2 ca

TRISE phi bng 1 cc chn ny c cu hnh l cc chn ng vo. Trong ch

PSP, bm ng vo Port E l linh kin hTTL.

Cc chn ca Port E cn c chc nng Analog, ti mode ny, cc chn ny s

c c vl gi tr0

Hnh 6.9: Thanh ghi TrisE v PortE

6.1.3 iu khin ng c bng PWM

iu khin tc ng c DC ngi ta c thdng nhiu phng php khc

nhau trong c mt phng php ht sc quan trng v thng dng l phng

php iu chrng xung kch (PWM), c ngha l thay i rng xung kchiu khin linh kin ng ngt (SCR hay Transistor), t iu khin tc

ng c. BPWM c thto ra tcc linh kin in t.

PIC16F887A iu khin ng c quay thun-nghch v thay i tc , ta s

dng biu chrng xung (PWM) tch hp sn bn trong PIC vi 2 ng ra

xung ti hai chn CCP1(17) v CCP2 (16) . Ti cc chn ny khi hot ng sxut

chui xung vung , rng iu chnh c ddng. Xung ra ny dng to tn

hiu ng ngt Trasistor trong mch ng lc, vi rng xc nh sto ra mt

in p trung bnh xc nh. Thay i rng xung sthay i in p trung bnh

v do thay i c tc ng c.

c thsdng c bPWM trc ht n phi c khi to chPWM

bng lnh:

setup_ccpx (CCP_PWM) vi x = 1,2


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BPWM hot ng phi c shtrca Timer 2 , y l Timer 8-bit c

bchia trc. Ng vo xung Clock (=fosc/4) c tuchn hschia trc l:

1:1, 1:4, 1:16 c la chn bng cc bit iu khin T2CKPS1:T2CKPS2.

Lnh khi to Timer2 v cng l to chu kxung cho bPWM l:

setup_timer_2(mode,period,postscale)

vi: -Modec thchn mt trong cc hnh thc sau:

T2_DISABLED, T2_DIV_BY_1 T2_DIV_BY_4, T2_DIV_BY_16

-Periodl mt snguyn (0 255) xc nh khi no th xung

clock reset.

-Postscalel s(116) xc nh c bao nhiu ln reset trc

mt ngt: 1 c ngha l 1 ln, 2 ngha l 2 ln

Chc nng ca lnh ny l to ra chu kxung v c tnh nh sau:

T = (1/fosc)*4*t2_div*(period+1)

Xt v d:

Lnh: setup_timer_2(T2_div_by_4,0xc0,2)

vi thch anh 10MHz , Timer2 stng mi 1.6us ( 4*4*1/10e6), sbtrn

mi 307.2us (1.6*192), v sbngt mi 714.4us ( 307.2*2).

y chu kxung l T = (1/10e6)*4*4*(192+1) = 153.6us.

Cthtrong bi, mun to chu kxung 1ms ta khi to Timer2 nh sau:

setup_timer_2(T2_div_by_16,154,1)

Khi y T= (1/10e6)*4*16*(154+1) = 0.992ms = 1ms.

Tip theo, to xung bng lnh:


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6.2 Phn mm bin dch CCS

C nhiu trnh bin dch cho PIC nh CCS, MikroC,Hi-Tech C, MPLAB IDE

y sinh vin sdng trnh bin dch CCS v tnh phbin cng nh khnng htr

rt tt.

CCS l trnh bin dch dng ngn ngC lp trnh cho Vi XL PIC, gip nhanh

chng trong vic vit chng trnh hn so vi ngn ngAssembly. CCS htr

son tho v bin dch cho 3 dng PIC:

PCB cho dng PIC 12-bit opcodes.

PCM cho dng PIC 14-bit opcodes.

PCH cho dng PIC 16 v 18 bit

M lnh c ti u khi bin dch

CCS c cha rt nhiu hm phc vcho cc mc ch v c rt nhiu cch lp

trnh m cho cng mt vn dn n khc nhau tc thc thi m, dai

chng trnh.

Chng trnh CCS cho php vic phi hp Assembly cng vi C cho chng trnh

c thnhanh chng gii quyt vn . Nu chvit bng C hoc Assembly skh

khn hoc khng gii quyt c.

CCS cung cp cc cng ctin ch gim st hot ng chng trnh nh : C/ASM

list: cho php xem m ASM ca file bin dch, gip qun l m v nm c cch

thc m sinh ra v chy nh thno

Mt sdng tp tin thng thng khi sdng chng trnh CCS:

.C: l tp tin ngun cha code ngun vit bng C. .h: l tp tin khai bo cc chn sdng, cc thanh ghi, cc hm v nhng

lp phkhc.

.pjt: l file project cha tt cc ni dung lin quan n project.

.hex: chng trnh bin dch chnp cho vi xl.

Khi to mt Project:

Tgiao din chng trnh chn Project ->PicWizard.


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6.3 Giao tip RS232

Vn giao tip gia PC v vi iu khin rt quan trng trong cc ng dng iu

khin, o lng... Ghp ni qua cng ni tip RS232 l mt trong nhng kthut csdng rng ri ghp ni cc thit bngoi vi vi my tnh.N l mt chun giao tip

ni tip dng nh dng khng ng b, kt ni nhiu nht l 2 thit b, chiu di kt ni

ln nht cho php m bo dliu l 12.5 n 25.4m, tc 20kbit/s i khi l tc

115kbit/s vi mt sthit bc bit. ngha ca chun truyn thng ni tip ngha l

trong mt thi im chc mt bit c gi i dc theo ng truyn.

6.3.1 u im ca giao tip ni tip RS232

+ Khnng chng nhiu ca cc cng ni tip cao

+ Thit bngoi vi c ththo lp ngay ckhi my tnh ang c cp in

+ Cc mch in n gin c thnhn c in p ngun nui qua cng ni tip

6.3.2 Cng RS232 trn PC

Hu ht cc my tnh c nhn hin nay u c trang bt nht l 1 cng Com hay cng

ni tip RS232. Slng cng Com c thln ti 4 ty tng loi main my tnh. Khi

cc cng Com c nh du l Com 1, Com 2, Com 3...Trn c 2 loi u ni

c sdng cho cng ni tip RS232 loi 9 chn (DB9) hoc 25 chn (DB25). Tuy hai

loi u ni ny c cng song song nhng hai loi u ni ny c phn bit bi cng

c (DB9) v cng ci (DB25)

Ta xt s chn cng Com 9 chn:

Hnh 6.12: Cng com 9 chn


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Chc nng ca cc chn nh sau:

+ chn 1 : Data Carrier Detect (DCD) : Pht tn hiu mang dliu

+ chn 2: Receive Data (RxD) : Nhn dliu

+ chn 3 : Transmit Data (TxD) : Truyn dliu

+ chn 4 : Data Termial Ready (DTR) : u cui dliu sn sng c kch hot bi b

phn khi mun truyn dliu

+ chn 5 : Singal Ground ( SG) : Mass ca tn hiu

+ chn 6 : Data Set Ready (DSR) : Dliu sn sng, c kch hot bi btruyn khi n

sn sng nhn dliu

+ chn 7 : Request to Send : yu cu gi, btruyn t ng ny ln mc hot ng khisn sng truyn dliu

+ chn 8 : Clear To Send (CTS) : Xa gi, bnhn t ng ny ln mc kch hot

ng thng bo cho btruyn l n sn sng nhn tn hiu

+ chn 9 : Ring Indicate (RI) : Bo chung cho bit l bnhn ang nhn tn hiu rung

chung

6.3.3 Mch giao tip RS232 dng IC Max232Max232 l IC chuyn dng cho giao tip gia RS232 v thit bngoi vi. Max232 l IC

ca hng Maxim. y l IC chay n nh v c sdng phbin trong cc mch giao

tip chun RS232. Gi thnh ca Max232 ph hp (12K hay 10K) v tch hp trong

hai knh truyn cho chun RS232. Dng tn hiu c thit kcho chun RS232 . Mi

u truyn ra v cng nhn tn hiu u c bo vchng li sphng tnh in ( hnh

nh l 15KV). Ngoi ra Max232 cn c thit kvi ngun +5V cung cp ngun cng

sut nh.

y l mch giao tip 1 knh dng Max232.

Mch giao tip nh sau :


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Hnh 6.13: Mch RS232 dng IC MAX232

Hnh 6.14: Cp chuyn i tUsb sang Com


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Chng 7: Thit kv Gii Thut GVHD: Ks L Ngc nh


CHNG 7:

THIT KV GII THUT

7.1Thit kphn cng

7.1.1 Mch sdng iu khin xe:

Mch Ngun:

Hnh 7.1: S nguyn l mch ngun 5VDC

Hnh 7.2: Mch ngun 5VDC

Sinh vin sdng mch ngun 5V DC cp ngun cho Vi XL. Dng u vo

l pin 9V DC, ng ra 5V DC.

Mch iu Khin:

o S nguyn l:


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Hnh 7.6: S mch cng sut


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7.1.2 Ton cnh m hnh:

Hnh 7.8: Phn khung robot

Hnh 7.9: M hnh robot hon chnh

M hnh gm khung c kh, 2 ng c DC gn pha di, 2 bnh sau c truyn ng

bi dy ai v 2 bnh trc l bnh xe omni linh hot khi chuyn hng.

Sdng ng c DC vi cc thng s:

- Cng sut 12V-60W

- Tc ln nht: 3000 vng/pht

- ng c khng ko trc tip bnh xe m thng qua c cu truyn ng ai.

truyn ng, ta s dng mt buli c ng knh bng 1/6 ng knh bnh

xe. Nn buli xem nh mt bgim tc


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nh tc ng vo

Adaboost

N

Y Mng

Neural

PP hnh hc RS232

PP Stereo vision

7.2.2 Gii Thut XL nh:

7.2.2.1Qu trnh chung

- Tm ti chxc nh bin sca mc tiu, thu hnh nh vtcamera

- Nhn dng bin sbng gii thut Adaboost, tch ring vng cha bin s(c

cha mt t vng nn) (chi tit ti chng 4). Nu khng nhn c bin squay

li bc u tin.- Dng phng php Canny lc bin nh v phng php Hough Line xc nh gc

nghing ca bin sso vi khung nh. Xoay bin svhnh chnht. (chi tit ti

chng 3). Nu xoay bli quay li bc u tin.

- Xc nh ta ca bin sv tch ring bin s( khng cha nn ) (chi tit ti

chng 3)

- Tch tng k tv sa vdng chun u vo mng neural.

-

nh xnh k tv svo ma trn. Nhn dng k tv sbng mng neural ( chi

tit ti chng 5) v lu vo c sdliu. Nu nhn din li quay li bc u

tin.

- Tnh khong cch tcamera ti bin sbng phng php stereo vision v

phng php hnh hc. Do tnh p ng nhanh v gii thut hiu qunn sinh vin

dng phng php hnh hc lm phng php chnh .

-

Xut k txung vi xl iu khin robot

Nhn dng ktv lu vo

c sdliu

Pht hinbin s

Tnh khongcch ti bin

s

iu khinng c theokhong cch

Giao din i ukhin (VC++)


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Xt nh c din tch 250*200 pixel. Bt u t im nh x, y u tinc ta (0,0).

Qut n ht chiu ngang (250 gi tr x)canh trn mt gi tr y ca nh (qut trn 1

hng).Nu l pht hin im en th lu gi tr y l nh ca hng u tin. Chnh l gii

hn trn ca dng th 1.Nu qut ht 250 gi tr ca x m khng thyim en no

th tng y= y+1 v khi ng li x qut hngngang tip theo.

Tip tc qu trnh qut tng hng nh vy. Mi lnpht hin im en l lu li gi

tr y.

o

Nu khng pht hin im en no th nh du gi tr y-1 l gii hn dica dng th 1. V tng s dng, xt dng tip theo.

o

Nu vn pht hin thy im en tng y v khi ng li x xt hng ngang tip

theo.

Bt u t gii hn di ca dng th 1tm thy sau cng lp li t cc bc tm

dng k tip.

Nu y bng chiu cao ca nh(200) th dng.

Gii hn trn Gii hn di

Tch dng

b.Tch tng k tvs:

Bt u t k t u tin ca hng trn cng vi gi tr x u tin.

Qut ht chiu rng vimt gi tr y.

7 2-L9

3 1 3 7


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Hnh 7.13: M hnh ha thut ton c lng khong cch

Sinh vin tch hp vo hthng thut ton c lng khong cch gia camera vi

bin sxe c pht hin. Thut ton ny c dng c lng khong cch gia

camera v i tng bin sxe da vo thng slin quan nh: chiu di tiu cca

camera, thng squy i tpixel ra milimet ti mt phng tiu cv ln thc tin

hnh ca bin sxe.

Cth, cng thc c lng khong cch theo l thuyt c tnh theo cng thc:

Z

Xfx

x

XfZ

Vi,

f : l chiu di tiu cca camera

Z : l chiu di c lng (cn tm) gia camera n i tng

X : l kch thc thc tca i tng (n vchiu di)

x : l kch thc nh ca i tng (pixel)

Trong thc t, khong cch c lng cn cn mt thng squy i n vpixel

ra mmtrong mt phng tiu cchorhoc cvert.


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Chng 8: Kt QuV Hng Pht Trin GVHD: Ks L Ngc nh

SVTH: L c H

nh - 40700703 Trang 96

Nt chc nng NHN DINsly hnh nh twebcam vv gn

vo khung hin th1. ng thi trin khai thut ton Adaboost pht

hin ra bin s. Sau khi pht hin c bin s, chng trnh sto mt

vin bao quanh bin sv trch xut bin s(c mt t nn) sang

khung hin th2.

Hnh 8.2: Pht hin bin s

Sau khi trch xut c bin s, ta thy bin sbnghing so vi ng

bin ca khung hnh. Nt chc nng XOAY NH slc bin cabin sv dng phng php houghline tnh gc nghing sau xoay

bin svdng hnh chnht. Khi a bin svdng hnh chnht,

chng trnh strch xut tip phn bin s(khng c nn).


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SVTH: L c H

nh - 40700703 Trang 98

Nt chc nng TCH Sc cc nhim vsau:

o Chnh kch thc bin svkch thc 250*200 pixel

o Tch bin sthnh 2 dng

o

Tch tng k tv s

o Lu kt qutch vo cc trong khung Kt QuNhn Din

Hnh 8.6: Tch dng 1

Hnh 8.7: Tch dng 2


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SVTH: L c H

nh - 40700703 Trang 100

Hnh 8.9: Kt qunhn din bng mng neural

2 nt chc nng CALIB v KHONG CCH dng hiu chnh

webcam v o khong cch khi dng phng php stereo vision. Sinh

vin strnh by trong phn mc lc.

2 nt chc nng GHI DLIU v C DLIU dng nhp

v c dliu bng tay. Khi ghi dliu cn in sID v ni dung d

liu (cc k ttrn bin s) khung kt qu. Khi c dliu chcn gisID c lu, sau ni dung dliu sc gi ra.

Nt chc nng BM UI ly hnh nh thu vtwebcam gn ln

khung hin th1. Thc hin vic o khong cch bng phng php

hnh hc v xut k txung vi xl iu khin robot.


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SVTH: L c H

nh - 40700703 Trang 102

Nt c hnh tm dng c nhim vtm dng tt ccc hot ng ca

chng trnh. Tt ht cc ca shin th.

8.1.2 Kt qum hnh

Hnh 8.11: M hnh phn cng hon chnh

M hnh phn cng gm:

Khung robot bng c kh, 2 ng c DC (12V,60W)

Cc mch vn hnh: mch ngun 5V, mch iu khin, mch cng sut.

Laptop Acer 5738, Window 7 Ultimate

Webcam Quick Cam C210 (640*480, 1.3 triu pixel, 15fps)

ng chy cho xe, ray trt, thanh trt, bng chia khong cch.

8.2

Thng k tl

Sinh vin thnghim nhn dng ti chgixe khu nh v trong trng.

- Vi c2 iu kin nh sng trong nh v ngoi tri.

-

Gc quan st v thu hnh vtwebcam i vi bin sxe theo cc phng

x,y, z trong khong 25o.


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SVTH: L c H

nh - 40700703 Trang 103

Hnh 8.12a: Mt shnh nh thnghim nhn dng vi nh sng trong nh

Hnh 8.12b:Mt shnh nh thnghim nhn dng vi nh sng ngoi tri


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SVTH: L c H

nh - 40700703 Trang 104

nh gi chnh xc trong nhn dng ca phn mm lun vn

Mi trng Slng bin sxe

thnghim

Slng bin sxe

c pht hin

Tlnhn din ng

k tv s

Trong nh 43 42 (98%) 95%

Ngoi tri (nngnh)

45 42 (93%) 90%

Ngoi tri (nnggt)

40 32 (83%) 82%

Bng 8.1: Thng k tlnhn dng

i vi iu kin nh sng ngoi tri tlpht hin v nhn din ng bin sthp

hn so vi khi xt trong nh. Nht l khi tri nng gt bin sbchi, kt qupht hin

v nhn din km i nhiu.

i vi iu kin nh sng va phi (trong nh hoc tri nng nh) tlpht hin v

nhn din rt cao. c bit khi bin svtr thng khng mo v khng bbn th pht

hin v nhn din chnh xc.

H thng vn c th pht hinbin sxe n khibin sxe cn kch thc ti thiu

quy nh trong dng m lnh pht hin(50*40 pixel).

nh gi chnh xc trong o khong cch ca phn mm lun vn


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SVTH: L c H

nh - 40700703 Trang 106

- Khong cch o c cn sai s.

8.5Hng pht trin ca ti:

-

Thut ton Adaboost tuy cho kt qunhn din rt nhanh v chnh xc tuy

nhin khi thay i gc quay (>30o) kt qunhn dng skm i nhiu. Cn tm

hiu thm cc c trng mi kt quhun luyn c tt hn.

- Thu thp thm cc bin smu a dng dliu hun luyn.

- Tm ra mt cng thc tnh khong cch c t sai shn.

-

Sdng ng c c encoder kt hp thut ton PID iu khin ng c

c tt hn.


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Ti Liu Tham Kho GVHD: Ks L Ngc nh


Ti Liu Tham Kho

[1] Vng Nht Thy (2010).XLnh Bng Thut Ton Adaboost Nhn Dng Bin S

Xe Thng Minh. Lun Vn i Hc, i Hc Bch Khoa TPHCM.

[2] V Hng Phong (2008).Nhn DngXe Trn C SThGic My Tnh. Lun Vn

Thc S, i Hc Bch Khoa TPHCM.

[3] L Ngc Thch.Lp Trnh Window Vi MFC Microsoft Visual C++ 6.0. Nh Xut

Bn Thng K.

[4] Davis Chapman (2001). Teach Yourself Visual C++6 in 21 day. Sams Publishing,

Indianapolis, Indiana, 46290 USA.

[5] Ng Hi Bc (2006).Lp trnh giao tip my tnh qua cng RS232. Din n

picvietnam.com

[6] Bi Quang Chin (2007). ng dng mng neural trong nhn dang k t.Lun Vn

i Hc, i Hc Dn Lp Hi Phng.

[7] Nguyn Xun c (2010).iu khin robot di ng dng th vin OpenCV. Lun

Vn i Hc, i Hc Cng Ngh.

[8] OpenCVs Document (2009). CV Reference Manual. Version 2.0

[9] Gary Bradski & Adrian Kaebler.Learning OpenCV Computer Vision with the

OpenCV Library. OReilly.

[10] TS. Nguyn c Thnh (2005).o lng v iu khin bng my tnh. Nh Xut

Bn i Hc Quc Gia TpHCM

[11] OpenCVs Document (2009).Rapid Object Detection Uwith A Cascade of Boosted

Classifiers Based on Haar-like Features. Version2.0

[12] Tutorial: OpenCV haartraining:http://note.sonots.com/SciSoftware/haartraining.html

[13] OpenCV:http://www.shervinemami.co.cc/openCV.html

[14] Detect objects using Haar-like features: http://www.computer-vision-

software.com/blog/2009/06/opencv-haartraining-detect-objects-using-haar-like-features/
http://note.sonots.com/SciSoftware

Documents

Thuật Toán Adaboost Và Mạng Neural Trong Nhận Dạng Và Bám Đuổi Biển Số Xe