Nghiên cứu so sánh các thuật toán xử lý ảnh tính độ sâu ảnh stereo ứng dụng trong hệ thống camera thị giác

Tp ch Khoa hc HQGHN: Khoa hc T nhin v Cng ngh, Tp 30, S 3 (2014) 26-48

26

Nghin cu so snh cc thut ton x l nh tnh su nh stereo ng dng trong h thng camera th gic

Bch Ngc Minh*

Trung tm Pht trin i hc Quc gia H Ni, 144 Xun Thy, H Ni, Vit Nam

Nhn ngy 16 thng 7 nm 2014 Chnh sa ngy 18 thng 8 nm 2014; Chp nhn ng ngy 22 thng 9 nm 2014

Tm tt: C ba phng php c bn so snh s tng hp gia hai nh l SAD, SSD v NCC.

Phng php NCC s dng s tng quan cho gia cc im nh nn cc php ton rt phc tp.

Chng bao gm php ton bnh phng, tng, tch cc tng, khai cn nn vic thc hin chc chn

rt tn thi gian. Cn hai phng php SAD v SSD c phc tp ca thut ton khng khc

bit qu ln nn chng ta cn lm mt thc nghim kim chng cht lng bn su v

tc thc hin. T chn ra mt phng php thch hp hn

So snh thi gian chy gia hai gii thut SAD v SSD cho thy vic la chn cc thut ton

SAD l hp l hn, bi v cc thut ton SSD cn gn gp i thi gian chy. Phng php SAD

c th gii quyt vn i vi vic tm su trong nh 3D. Mt im khng gian ly nh

hai ng knh my ti hai v tr khc nhau. Chnh v th nn trc khi tm c su ca im

nh, ta cn tm c cc im nh tng ng . Phng php SAD l phng php n gin nht

tm c im nh .

Phng php SAD li c nhiu cch tnh ton, tnh theo phng php SAD truyn thng,

phng php SAD iu chnh (da vo bin nh), phng php SAD phn on ( phn vng nh).

y ta li la chn gia 2 phng php SAD iu chnh v SAD phn on gim 20% so vi

SAD truyn thng.

Tip theo chng ta xem xt cc thut ton SAD phn vng lai c to ra bi s kt hp ca

hai k thut: Belief Propagation v cc thut ton phn on Mean Shift. Cch tip cn ny kt

hp nhng u im ca c hai phng php phn on. Cc thut ton Mean Shift cho kt qu

nhanh chng v Belief Propagation thc hin phn on rt chnh xc.

T kha: Phn vng nh, Belief Propagation, Mean Shift, SAD , hnh nh 3D.

1. Gii thiu*

Mt xu hng pht trin mi l r bt s

dng camera th gic quan st nh mt

ngi. Mc d vic chit xut d liu t nh th

_______ * T.: 84-913550789 Email:[email protected]. Email:[email protected].

gic l kh khn hn l dng cm bin nhng

b li th cch thc ny cung cp cho r bt v

con ngi nhng d liu trc quan sinh ng v

y .

Khi x l tn hiu nh stereo th gic

thng c hai khu (Hnh 1).

B.N. Minh / Tp ch Khoa hc HQGHN: Khoa hc T nhin v Cng ngh, Tp 30, S 3 (2014) 26-48 27

* Khu u tin l khu tin x l c nhim

v ly ra cc d liu c cha thng tin hu ch

cho vic pht trin cc ng dng th gic stereo

thi gian thc.

* Khu th hai cc ng dng th gic nh

ng dng ti to mi trng 3D, tm ng,

pht hin i tng

Hnh 1. Qu trnh x l d liu nh stereo th gic.

Trong khu tin x l, c mt c im

chnh l khi lng d liu thu thp bng

camera rt ln (ln hn nhiu ln so vi d liu

thu thp bng cm bin) cn c x l.

Mi cch gii quyt mi u phi c

pht trin trn mt nn tng sn c. phn tip,

cc k thut c bn ca x l nh 3D s c

a ra lm c s pht trin cho cc thut

ton v sau. Bc u tin, chng ta s tm hiu

v nh 3D v my quay 3D, nn tng c s u

tin ca h thng. Sau , cc k thut x l

trch ra ni dung ca nh s c bn n. Cc

thut ton c bn da vo m c cc

nghin cu hon thin hn.

1.1. nh 3D: L nh m bn thn n c cha ni dung v chiu su. Cc im nh ngoi cc gi tr v mu sc, ta theo hai trc c bn cn c gi tr v chiu su. to nn c tm nh 3D, ngi ta thc hin ng thi hai tm nh v cng mt ni dung nhng khc hng.

Hnh 2. Mt cnh trong phim 3D.

B.N. Minh / Tp ch Khoa hc HQGHN: Khoa hc T nhin v Cng ngh, Tp 30, S 3 (2014) 26-48

28

(Hnh 2) th hin mt tm nh 3D c

theo di bng mt knh chuyn dng. nh trn

c cu to t hai tm nh khc nhau c

trn bi 2 di mu khc nhau. Khi nhn nh trn

bng knh mt chuyn dng, mi mt ca ngi

xem s thy mt nh. S chnh lch v tr trong

2 tm nh nhn thy s to nn cm gic v

su cho ngi xem. Thc t, khi tch hai tm

nh ca mt nh 3D, chng ta s c th nhn

c nhng bc nh tng t nh trong ( Hnh 3).

nh 3D c nhiu ng dng hn l gii

tr. N c kh nng lu tr su im nh nn

cng c s dng cho cc ng dng yu cu

su im nh. Ni cch khc, t mt tm nh

3D, chng ta c th m t li khng gian hoc

ly nhng thng tin hu ch t su im nh

[1]. Cc i tng 3D cng c th c trch ra

t mt tm nh 3D.

a b

Hnh 3. nh 3D sau khi tch ra. a: nh nhn thy mt tri; b: nh nhn thy mt phi

1.2. Stereo camera: L thit b thu nh 3D hoc thu phim 3D. V c bn, stereo camera cng ging nhng my nh hoc my quay chuyn dng khc, nhng n c hai ng knh mc song song (

Hinh 4)[2]. Hai ng knh ca mt stereo-camera c s dng ly hai hnh nh trong mt nh 3D.

Hnh 4. H thng Stereo camera Bumblebee [3].


(Hnh 5). th hin hot ng ca mt stereo

camera [3]. Cc chi tit s c thu vo 2 tm

nh thng qua 2 ng knh ca camera cng mt

lc. Lc ny, ta ca im nh thu c trn

hai tm s c mt lch nht nh, ta gi

lch l .

Hnh 5. Hot ng ca stereo camera.

Ta c:

= x1 x2 (1-1)

V khong cch t im A n camera s

c tnh:

Nh vy, t cc ta nh thu c ca

im A trn hai tm nh tri phi, ta s thu

c khong cch t camera ti im A.

Khong cch ny cn c gi l su im

nh k hiu bng z.

1.3.Tnh ton bn chnh lch: L mt trong nhng vn quan trng trong th gic my tnh 3D. Mt s lng ln cc thut ton c xut gii quyt vn ny [4],[5]. Mt trong nhng phng php tng i mi l Ci thin tnh ton Bn su t hnh nh stereo theo phng php lai.

i vi cc cp hnh nh stereo c

chnh sa epipolar, mi im trong hnh nh

bn tri nm trn ng nm ngang ( ng

epipolar ) c th c im nh tng ng trong

hnh nh bn phi. Cch tip cn ny c s

dng lm gim khng gian tm kim chiu

su bn thut ton tnh ton. Chiu su ca

mt im nh l khong cch im khng gian

tng ng ti trung tm my nh. c tnh

bn su v pht hin cc i tng 3D,

cc im nh tng ng trong nhng nh tri v

nh phi cn c pht hin. Thut ton ny

bao gm cc giai on sau y (Hnh 6) :

1. Thu thp hnh nh,

2. Hnh hc Epipolar v ci thin hnh nh,

3. Phn on,

4. Thut ton ph hp stereo,

5. c lng bn su.

u tin, bin dng xuyn tm v tip tuyn

ca ng knh c loi b bng cch hiu chnh

my nh bi cc thng s bn trong v bn

ngoi my nh. lm c iu ny cn c s

hiu bit v cc thng s my nh vi mc ch

khc phc c hai hnh nh. Sau khi hiu chnh,

hnh nh c tch ra thnh cc khu vc bng

cch s dng cc thut ton phn chia lai c

xut. Cui cng, thut ton ph hp stereo

c p dng trn cc hnh nh phn on tri

v phi vi mc ch tm tt c cc tng

quan (im ph hp) v gn chiu su cho tng

phn on. u ra ca thut ton ph hp

stereo l cc bn su.

(1-2)


30

Hnh 6. Thut ton SAD phn vng [6].

Trong phn tip theo, mc 2.1 trnh by v

tng quan v hiu chun my nh c bn. Hnh

nh ci tin da trn phn on c m t

trong mc 2.3. Phng php phn on Mean

Shift v Belief Propagation c trnh by

trong mc 6 v mc 7. Ti mc 8 trnh by v

thut ton SAD phn vng lai. Cui cng l kt

qu thc nghim v kt lun c trnh by

mc 9 v mc 10.

2. Ci thin hnh nh

2.1. Hiu chun my nh: p dng cc k thut khc nhau cho nh stereo vi mt mc hp l chnh xc, iu quan trng l hiu chnh h thng camera. N l mt qu trnh tm kim cc thng s bn trong v bn ngoi ca my nh. Cc phng php hiu chun c in da trn cc mu hiu chun c bit chun b, cc i tng vi kch thc v v tr c bit n trong mt h ta nht nh. Sau , cc tnh nng, chng hn nh gc v ng, c chit xut t mt hnh nh ca m hnh chun. i tng vi cc tnh nng c ngha thng

c chn hiu chnh c mt cch r rng cc v tr ca chng. Ngi ta thng dng mt bn c n gin c th t c mc ch ny.

2.2. Chnh sa hinh nh: Chnh sa hnh nh (Hnh 7) l cn thit gim phc tp tnh ton im nh tng ng trong hnh nh tri v bn phi. Mc ch ca vic ci thin hnh nh l tm ng epipolar ca hai hnh nh theo lin kt chiu ngang. iu ny c th c thc hin bng cch s dng cc bin i tuyn tnh xoay, dch v nghing hnh nh. Cc thng s ni b camera v thng tin v nh hng v v tr my nh c s dng trong cc php bin i.

Cc im 3D c phn chiu thnh cc

im trong hnh nh stereo tri v phi. Sau khi

ci thin theo (Hnh 8), cc ng epipolar ca

hai im phn chiu l song song theo chiu

ngang v lin kt dc theo mt phng hnh nh

mi. Cc im c nm trn cng mt ng

dy epipolar [7]. Do vn ph hp stereo

c gim xung tm kim mt chiu dc theo

cc ng ngang, thay v tm kim hai chiu

nh n c hin th trong (Hnh 8) [8],[9].

Tri Tri

Phi su

nh stereo ph hp

Bn su

Phn khc Hiu chnh nh

Phi

M hnh hiu chun

(Bn c)

Cc thng s hiu chun

Hnh nh vo


Hnh 7. nh stereo trc khi chnh sa.

Hnh 8. nh stereo sau khi chnh sa.

2.3. Phn on hinh nh mu: Trong phn ny, hai phng php phn chia mu sc c m t: Belief Propagation, Mean Shift. Mc tiu ca vic phn vng nh l chia ton b hnh nh thnh mt tp hp cc phn on bao gm cc hnh nh. Cc phn on cui cng phi p ng y bn iu kin sau [10]:

1.

2. Vi mi i v j, , tn ti

3. Vi th bt buc

4. Vi mi , tn ti

trong R i din cho ton b hnh nh, Ri (i

= 1, 2,..., n) l cc phn on khng rng,

khng chung nhau ca R, P(Ri) l thuc tnh

ging nhau ca tt c cc yu t trong Ri v 0

i din cho mt tp rng. Tng kt cng tc

phn on phi bao gm tt c cc im nh

trong hnh nh. y l iu kin tin quyt.

iu kin th hai th hin cc phn on khc

nhau khng chng cho nhau. iu kin th ba

th hin rng cc im nh trong cng phn

ng epipolar

ng epipolar

Trung tm chiu

Ca s tm kim im nh tng ng


32

on phi c chung thuc tnh. Cc thuc tnh

phi khc nhau l iu kin cui cng.

C mt s thut ton c xut

gii quyt vn ny. Tuy nhin, tt c cc

thut ton ny u s dng hm chi ph kt hp

thit lp s tng ng gia hai im nh. C

ba phng php ph bin nht l phng php

da trn s khc bit cng tuyt i (AD),

phng php da trn s khc bit cng

bnh phng (SD) v phng php da trn s

tng quan cho chun (NCC).

2.4. Cc phng php th gic stereo chnh c th hin v mt ton hc nh sau:

1- Phng php tng s khc bit tuyt i (SAD - Sum of Absolute Differences):

(2-3)

Theo cng thc (2-3), vic tnh gi tr chnh

lch ca im (x,y) c thc hin bng php

tnh hiu trong ca s W. Do thut ton n

gin. Ca s W v phm vi chnh lch d cng

ln th s php tnh tng. Thng thng c th

thc tnh SAD vi ca s 3x3, hoc 5x5 hoc

7x7 hoc 11x11. Phm vi chnh lch d thng

chn di 120 vi cc gi tr tham kho nh 16,

50, 128. [11-13].

2- Phng php tng bnh phng khc bit (SSD Sum of Squared Differences):

(2-4)

Phng php ny tnh tng ca cc bnh

phng ca cc hiu nn xut hin thm php

nhn trc khi tnh tng. Do phc tp

tng ln ng k [19].

3- Phng php da trn s tng quan cho chun (NCC)

(2-5)

Trong Il, Ir l nhng gi tr cng

trong hnh nh tri v phi, (x, y) l ta ca

im nh, d l gi tr sai lch c xem xt v

W l ca s phc hp. Vic la chn cc gi tr

sai lch thch hp cho mi im nh c thc

hin sau .

Phng php ny c phc tp cao nht

v xut hin cc php ton tiu tn nhiu ti

nguyn ca my tnh nh php bnh phng,

khai cn. Do vic ng dng ca thut ton

ny trong cc h thng thi gian thc l khng

kh thi.

(2-6)

tc l, cho mi im nh (x, y) v cho gi tr

khng i c s khc nhau d, chi ph ti thiu

c la chn. Phng trnh (2-6) c dng

cho phng php SAD. Tuy nhin, trong nhiu

trng hp la chn khc bit l mt qu trnh

lp i lp li, v chnh lch ca mi im

nh l ty thuc vo s chnh lch ca cc im

nh ln cn [14].

Cc thut ton phn vng lai l mt s kt

hp vi phng php SAD c p dng ph

hp vi hnh nh stereo tinh chnh cc bn

su cui cng . C hai, cc thut ton ph

hp vi m thanh stereo da trn phng php

m khng SAD phn on v cch tip cn lai


xut da trn phng php phn khc hybrid

l hiu qu. tin.Tp hnh nh c tnh ton

trn 2,8 GHz b x l Intel Core i5 vi 4 GB b

nh DDR3 v kit pht trin FPGA DE2 m

phng.

Kt qu thc nghim SAD

phn gii Ca s Thi gian(s)

400x266 3x3 46

400x266 5x5 58.5

400x266 9x9 105

Kt qu thc nghim SSD

phn gii Ca s Thi gian(s)

400x266 3x3 106.5

400x266 5x5 335

400x266 9x9 891

Thi gian tnh ton cho cc thut ton SAD

l khong 105 giy v cho phng php phn

vng lai 29 giy, tng ng. Cc thut ton

ph hp vi hnh nh stereo da trn SAD lai

c v l thut ton hiu qu hn sn xut

bn chnh lch sch hn vi cc khu vc

ng nht. Mt khc, cc thut ton ph hp

vi hnh nh stereo da trn phng php SAD

sn xut mt bn chiu su r rng v hin

trng. Hn na, n to ra mt cht lng cao

hn v t li gy ra bi tc phn on hnh nh.

N c p dng cho cc hnh nh stereo chp

bi my nh lp th ca chng ti. B d liu

th nghim ca chng ti bao gm 25 cp hnh

nh stereo thc s trong mu xm quy m vi

kch thc 800x600 pixels. (Hnh 28)

Kt qu l, cn thit c nhiu ln lp li

tm ra cc thit lp tt nht ca s chnh lch.

Giai on ny to nn s khc bit gia thut

ton a phng vi thut ton ton cc. Qu

trnh tnh ton thng thm mt bc na

kt qu tt hn gi l khu lc (Hnh 9).

Hnh 9. S khi tng qut ca mt thut ton tng ng stereo.

3. Phng php SAD truyn thng:

Hnh 10. S khi tng qut ca phng php SAD truyn thng.

nh tri

Tnh

SAD

Chuyn i

nh xm

Chuyn i

nh xm

nh phi

T h thng camera stereo

Bn chnh lch

La chn

chnh lch

Tp hp chi ph ph

hp

Sng lc kt qu

Tnh ton chi

ph ph hp

Hnh nh

u vo

Bn

chnh lch


34

Nh phn tch phn 2.4, phng php

SAD l phng php nhn din rt thun

tin. Song, bn cnh u im ca phng php

ny, n cn c mt s khuyt im v thi gian

p ng v xc sut li.

Cng thc (3-7) th hin tc ca thut

ton ny p dng vo vic tnh Bn chnh lch.

Trong cng thc ny, t l thi gian chy

chng trnh, S l s im cn tnh, W l kch

thc ca s tnh ton v L l khong cch yu

cu tnh ton. Vi cng thc trn, gi s c mi

1.5 triu php tnh hm chy trong 1 giy, tm

nh x l vi kch thc 640x480 pixel, kch

thc ca s l 5x5 pixel v khong cch thc

hin l 50 pixel.

Khi , thi gian php ton l 25.6 giy.

y l mt khong thi gian ln, hay ni cch

khc l tc tnh ton ca php ton l kh

chm.

a

b

c

d

e

f

Hnh 11. Cc kt qu tnh SAD thng thng. a) nh tri gc, b) nh phi gc, c) Bn chnh lch mong mun, d) Bn chnh lch tnh bng phng php SAD vi ca s 5x5, e) Bn chnh lch tnh bng phng php SAD vi ca s 7x7, f) Bn chnh lch tnh bng phng php SAD vi ca s 11x11.

Mc d tc tnh ton rt chm, kt qu

tnh ton li khng chnh xc hon ton. Li

ca phng php SAD rt thng xuyn xy ra

do nhm ln trong qu trnh tnh ton. (Hnh

11) th hin mt s kt qu tnh bn sai lch

bng phng php SAD vi cc ca s 5x5,

7x7 v 11x11 thc hin trn nh Teddy [14].

Nhn xt, ng vi cc hnh trn, li cc b

xy ra nhiu nhng thut ton s dng ca s

so snh nh. Tuy nhin, hnh dng ca cc vt

th trong thut ton li c gi gn nht vi

hnh dng thc ca n. S dng ca s ln hn

s cho li cc b t hn, nhng hnh dng ca

cc vt th li b sai st ng k so vi thc t.

Hn th na, cc li ln vn khng th gim

thiu trong thut ton ny.

(3-7)


Hnh12. Tc php ton SAD vi cc kch thc ca s khc nhau.

12) th hin thi gian ca thut ton o da

trn u vo l mt tm nh c kch thc

450x375. Nh vy, tc ca thut ton kh

b, khng thch hp cho mt h thng x l trn

robot, k c khi loi b tt c cc li.

Li ca phng php SAD l do u?

Phng php SAD da trn s so snh khc

bit gia cc ca s nh. Theo nh tng

thut ton th nh ca cc im hai tm nh l

ging nhau nht. Nh vy, kt qu tnh ton ca

thut ton ny thc s khng hiu qu cho h

thng dn ng chy trn robot. Nu thc s

trin khai mt h thng nh vy trn robot cu

h th s phi tn chi ph rt ln v kh nng

tnh ton m cha chc hiu qu. V vy,

phng php ny cn phi c ci thin c

c kt qu tt hn v ph hp hn cho h

thng thc.

4. Phng php SAD iu chnh:

Sau khi phn tch nhng nhc im ca

phng php xc nh bn chnh lch da

trn phng php SAD truyn thng, ti mun

xut mt phng php tt hn v cht lng

cng nh tc .

(Hnh 13) th hin cc bc ca phng

php mi nhm ly c bn chnh lch.

Nhng mc tip theo ca chng 3 s th hin

r tng bc ca phng php ny v ngha

ca chng.

4.1. Phng php SAD i vi ng bin

L phng php da trn phng php

SAD nhng ch p dng vi nhng im thuc

ng bin. Vi cch ny, ti k vng s c

c kt qu chnh xc hn vi tc tnh ton

cao hn.

Hnh 13. Phng php SAD iu chnh.


36

Hnh 14. S khi tng qut ca phng php SAD iu chnh.

Gi s c mt cch no , ti c th gim

s im trong tp hp d liu cn tnh xung

cn 20% so vi ban u. Nh vy, tc ca

thut ton c th s tng ln n 5 ln hay thi

gian tnh ton s gim xung 5 ln. Tht vy,

theo phng trnh (3 -7) nu S gim i 5 ln v

cc gi tr khc vn gi nguyn, ta s c t gim

5 ln. Nh vy, ti s tm nhng im ng tin

cy nht tnh ton bn chnh lch nhm

gim li v tng tc .

Hnh.15. ng bin cng l ng bao i tng.

Nhng im c chn l nhng im

mang tnh phn bit cao, hay ni cch khc l

kh b nhm ln vi nhng im khc. Khi

chn ng bin lm tp hp d liu tnh

ton, bc u ta cng c th trnh c s

nhm ln gy ra bi cc im ln cn, li nhiu

nht trong nhng php ton trc.

ng bin cn gip to ra kt qu ni suy

chnh xc hn v sau . Nh vy, khi c c

ton b ng bao ca i tng v su ca

tt c cc im trn n, ta c th suy ra su

ca nhng im cn li.

Di nhng l do trn, ti chn ng bin

l nhng im s c tnh ton su trc

tip. (Hnh 16) l mt s so snh kt qu tnh

bn chnh lch da trn ng bin l 20%

bc nh, ng bin l 30% bc nh v ton b

bc nh. Vi kt qu th hin trong (Hnh

16), chng ta rt ra mt s nhn xt:

* Kt qu ca thut ton chnh xc hn i

vi nhng ng bin. S ng bin tnh ton

cng nh, chnh xc cng cao.

* Khi s im lm ng bin c tnh

ton nh n mt ngng no th kch thc

ca s tnh ton khng cn nh hng n kt

qu tnh ton na.

Vi nhn xt th 2, ta hin nhin c th

gim kch thc ca s ly SAD i m vn k

vng c c kt qu c chnh xc cao.

nh tri

Tnh

SAD

Chuyn i nh xm

Chuyn i

nh xm

nh phi


Pht hin bin

nh

Pht hin bin

nh

Bn chnh

lch


Hnh 16. nh gi kt qu ca phng php SAD da trn ng bin.

4.2. Phng php trch chn ng bin mu

Phng php trch chn ng bin mu l

mt phng php ci tin hn so vi phng

php trch chn ng bin da trn nh xm.

S d phi trch chn ng bin mu v ng

bin nh xm khng th hin c ht cc

ng bao ca i tng. Cc nh xm khng

th th hin c ht cc tnh cht nh i vi

nh mu. (Hnh 17) th hin s khc bit gia

ng bin c ly t nh mu v ng bin

c ly t nh xm.

(Hnh 18) th hin l do ca s thiu ng

bin trong ng bin nh xm. Trong nh mu

hoc cc mng mu ca nh gc c nhng im

c s nhy bc ca mu sc hoc ng bin,

nhng trong nh xm khng c. Nh vy, thc

hin bt cc ng bin bng cc mng mu c

bn, ta s c cc ng bin kn hn v c

trng hn. Sau y s l cc bc xy dng

gii thut tm ng bin da trn cc mng

mu c bn:

* Bc 1: Ta coi 3 mng mu ging nh

nhng nh xm bnh thng khc, ta tm ng

bin bng ton t sobel.

* Bc 2: ng vi mi im ch c th c 1

gi tr nn ta s ly gi tr ng bin ca n

bng gi tr ln nht trong 3 gi tr tnh c

trn 3 mng mu.

Tnh ton SAD da trn 3 mng mu s

phi tn thi gian gp 3 ln so vi tnh ton

SAD da trn nh xm. Tht vy, nu coi mi

mu c bn tng ng vi mt nh xm, ta

s phi tnh SAD da trn 3 tm nh so v mt

tm. Nh vy, da theo cng thc (3-7), kch

thc ca s W s tng gp 3 khin thi gian

thc hin php ton t cng tng gp 3 ln, tc

php ton s gim i 3 ln.

Tuy nhin, da vo phng php ny, tc

php ton s khng b gim i 3 ln nh so

vi phng php SAD nh xm thng thng.

Tht vy, bi l mc d ng bin c ly

da trn 3 mng mu, mi im ch l ng

bin ca mt mng mu c bn. Nh vy, php

tnh SAD da vo im cng ch phi tnh

trn mt mng mu. V iu ny khin tc

thut ton lc ny khng b tng gp 3 ln.


38

a

b

c

d

Hnh 17. ng bin 20% s im bng phng php Sobel mu v xm. a) nh xm b) nh mu c) ng bin nh xm d) ng bin nh mu

a

b

c

d

e

Hnh 18. Cc mng mu ca hnh gc.

a)nh mu , b) nh xm , c) nh mu , d. nh mu xanh lc e. nh mu xanh lam


5. Phng php SAD phn vng

SAD phn vng l k thut s dng ni

suy mt bn su bao gm cc im

tnh c chun. S dng k thut ny trong

trng hp chng ta c th on c phm vi

ca nhng im cn tnh. Gi s mt im

c xc nh bn trong mt vt th m nhng

ng bin ca n c xc nh su.

Khi , tn ti mt xc sut cao rng nhng

im bn trong vt th s c su trong mt

phm vi nh xung quanh gi tr su ca cc

ng bin ca n. Khi , s gii hn su

tnh ton ca cc im ni suy c th lm mt

kh nng nhm ln gia im cho v cc

im bn ngoi.

Hnh 19. SAD phn on.

(Hnh 19) , gi thit su ca nhng

im thuc ng bin bao gm E1 v E2

tnh c v tnh chun. Khi , gi tr v

su ca A ch c th dao ng xung quanh cc

gi tr su ca E1 v E2 dn n kh nng

tnh ton su ca A c nng cao ln, mt

khc li khng b nhm ln vi mt im cng

c cu trc mu tng t l im B.

Hnh 20. S khi tng qut ca phng php SAD phn vng.

nh tri

Tnh

SAD

Chuyn i nh xm

Chuyn i nh xm

nh phi


Phn on

Phn on

Bn chnh

lch


40

Gi thit bin php ny khng c s

dng, khi nh i chiu c th xut hin

mt im ging vi im cn tnh nm ln

cn khong cch vi im B. Khi ny, thut

ton SAD c th a n s nhm ln gi tr

su ca A. im A c th c tnh nhm v

nh hng trc tip n cc im nm bn cnh n.

Tm li, phng php SAD phn on dng

tt trong trng hp ni suy da theo gi tr tnh

ng. S dng bin php ny gip gim li v tng

tc . Tnh ton bn chnh lch l mt trong

nhng vn quan trng trong th gic my tnh

3D. Mt trong nhng phng php tng i mi

l Ci thin tnh ton Bn su t hnh nh

stereo theo phng php lai.

C nhiu phng php tnh Bn chnh

lch, y ta nghin cu hai phng php ci

thin tc tnh ton ( SAD iu chnh v SAD

phn vng).

6. Belief Propagation

Belief Propagation l cc thut ton

c pht trin ch yu l vi mc ch tm

xc sut cn bin trong mng Bayes. Ngoi ra,

cc thut ton cng c th x l cc m hnh

ha khc nh m hnh Markov Random Field

(MRF), y l mi quan tm nht nh trong

vic ti u ha cc hm nng lng ton cc

c tm thy trong my tnh th gic. M hnh

MRF l m hnh th v hng, trong cc

nt i din cho cc bin ngu nhin. Xc sut

chung P(x1,..., xn) ca m hnh MRF pair-wise

c th c vit phn tch nh sau:

(6-6)

y xn i din cho cc nt ca th, Z

l hng s chun ha v cc sn phm trn ij l

hn cc nc lng ging gn nht trn mng

vung. Tim nng i(xiyi), biu din cho xc

sut cho mt trng thi nht nh xi Xi trong

nt i da trn quan st v tim nng ij (xi,xj)

biu th s ph thuc iu kin gia cc nt ln

cn. Bin quan st yi him khi c vit ra mt

cch r rng [15].

Thut ton Belief Propagation (BP) th hin

trong (Hnh 21) cc thng ip c chuyn i

trong mt m hnh ha thng qua mt lot

cc bn tin c gi i gia cc nt ln cn

xung quanh trong mt li hnh nh lin k 4.

Bn tin c cp nht trong cc ln lp. Trong

mi bc lp, mi im nh ca th lin k

tnh ton thng ip ca mnh, da trn kt qu

ca bc lp trc, v gi tin nhn mi ca n

ti tt c cc im nh lin k 4 (hng xm)

theo hnh thc song song [15].

Hnh 21. M hnh c bn cho phn vng nh.

M hnh c bn cho phn vng nh, nh th

hin trong (Hnh ), l mt th vi hai loi

nt: nt n (vng trn) v cc nt quan st (hnh

vung). l hm chuyn trng thi gia mt

cp nt trng thi n khc nhau v l hm o

lng gia cc nt trng thi n v nt d liu

quan st c. Trong BP, mi nt s gi mt

thng ip ti cc nt lng ging trong biu

din phn b xc sut [15].


7. Phng php Mean Shift:

Thut ton Mean Shift [16] c xut

bi Fukunaga v Hostetler. Cc thut ton da

trn mt c lng ht nhn [17]. Thut ton

ny l thut ton lp phi tham s. Cho mt tp

hp cc im d liu d-chiu c i din bi

cc gi tr xi, i = 1, 2,..., n trong d-chiu khng

gian Rd. S lng ca im xi thuc khu vc d-

chiu xung quanh x vi cnh di h c cho

bi:

(7-7)

trong h xc nh bn knh ca ht nhn

v K (x) l ht nhn hoc hm ca s. Nh vy,

c tnh mt ht nhn c cho bi:

(7-8)

Trong l ht

nhn i xng xuyn tm, l h s ht

nhn v c chun ha lin tc.Sau ,

phng trnh (7-10) c th c vit li :

(7-9)

c tnh ny c th c xem nh l

gradient ca xp x mt :

(7-10)

Mt ht nhn mi c nh ngha l

, trong

l hm ht nhn mi v l

hng s c chun ha. Sau khi thay th trong

phng trnh (7-12):

(7-13)

S dng phng trnh (7-13) thay i trung

bnh c xc nh:

(7-14)

Cc thut ton Mean Shift da trn vic tnh

ton lp i lp li vector dch trung bnh v thay

i c ngha v lin tc hin thc ha v tr

ht nhn bng phng trnh [15],[16]. xk +1 =

xk + m (XK). (7-15)

8. Thut ton SAD phn vng lai:

Trong phn vng nh, phng php lai kt

hp hai hoc nhiu hn cc thut ton phn

vng nh khc nhau [18]. y chng ta xem

xt cc thut ton lai c to ra bi s kt hp

ca hai k thut: Belief Propagation v cc

thut ton phn on Mean Shift nhanh chng

v rt chnh xc.

u tin, chng ti p dng cch lc hnh

nh bng thut ton Mean Shift. Bc ny rt

hu ch cho vic loi b ting n, lm mn v

phn vng nh. i vi mi im nh ca mt

hnh nh, tp hp cc pixel ln cn c xc

nh. Cho Xi l u vo v Yi hnh nh lc,

trong i = 1, 2,..., n. Cc thut ton lc bao

gm cc bc sau y [19],[20],[21]:


42

* Khi to , , .

* Tnh ton thng qua Shift bnh ch , ni

hi t im nh.

* Lu tr cc thnh phn ca mc xm ca

cc gi tr tnh ton ti ,

ni l thnh phn khng gian v , l

thnh phn phm vi.

Th hai, hnh nh c chia thnh cc on

s dng thut ton phm Mean Shift. Trong

bc th ba, thc hin sp x ng bao ca

cc phn on. Th t, cc phn on nh c

sp nhp vi nhau thnh nhng on tip gip

tng t nh hu ht cc phng php Belief

Propagation. Cui cng, chng ta tch hp thut

ton phn on lai xut vi thut ton ph

hp stereo SAD. Phng php ny SAD lai c

th cung cp kt qu bn su chnh xc

cao.

Hnh 22. Thut ton SAD lai.

Tnh ton lch: Trong mc ny, chng ta

din t qu trnh ca s so snh chnh lch ni

nh c a vo l nhng mnh (on) ln

u tin v sau nhng im c cng iu

kin bn tri v bn phi nh c tm thy.

y l mt tng c gii thch cho

vng 3D duy nht im P trn (hnh 23).

a ra khong cch ca vt c quan st bi 2

my quay cng nhn theo mt hng hng

nhng khong cch khc nhau c bit (nh

ngha) l ng c bn. Sau , vt th xut

hin v tr tng t trong c hai nh 3chiu.

Khong cch gia vt bn tri v bn phi

nh c bit (nh ngha) l khong chnh

lch d bi (8-16). XL v XR l ta x ca c

lng ta 3D cn trn nh phng bn tri v

bn phi l IL v IR .

(8-16)

(8-17)

Khi bn tri v bn phi ca nh phng

quay c c cng v tr phng, ta y ca 2

nh l bng nhau (yL = yR) v c chnh lch

ta ngang (trc x) l (xL - xR).[22]

iu ny c ngha l chnh lch c

tnh ton, cng c th thay i c khi

thay i thng s ca my quay: chiu di tiu

c f v khong cch ca ng c s B = 2l.


Hnh 23. Mt h thng stereo n gin .

9. Nhn xt v nh gi:

9.1. Phng php SAD truyn thng

Hnh 24. Mt s kt qu Bn chnh lch SAD truyn thng. a .Bn chnh lch vi ca s 5x5;

b. Bn chnh lch vi ca s 7x7; c. Bn chnh lch vi ca s 11x11;

Hnh 25. th thi gian, ph v chnh xc.

a) b) c)


44

9.2. Phng php SAD c iu chnh:

Hnh 26. Mt s kt qu thc hin tm SAD trn ng bin.

Hnh 27. th thi gian, ph v chnh xc.

Thi gian thc hin tnh bn chnh lch

theo phng php SAD iu chnh gim rt

nhiu so vi phng php SAD thng thng.

c.Phng php SAD phn vng:

Trong cuc th nghim tip theo, cc

phng php lai xut c th nghim trn

bn hnh nh stereo thc t c thc hin bi

h thng camera stereo. Thut ton ny c p

dng c tnh s chnh lch ca cc khi

9x9 t hnh nh bn tri tham chiu bng cch

tm kim cc khi ng c vin tng ng ca

hnh nh bn phi. Bn chnh lch cui cng

ca bn hnh nh lp th th nghim, c th l

sch, vt, khi lp phng v ta c th hin

trong (Hnh 28). C th, cc (Hnh 28-b) cho

thy cc bn khc bit c to ra bi thut

ton SAD m khng phn on v hnh. (Hnh

28-c) kt qu theo thut ton phn chia lai. Bn

chnh lch sn xut bi my nh ni

Bumblebee c hin th trong (Hnh 28-d).

a) b) c)


Hnh 28. Kt qu thc nghim trn bn nh th nghim mu xm.

a) Hnh nh tham kho, b) Bn chnh lch sau khi s dng thut ton SAD m khng phn on c) Kt qu ca thut ton SAD lai, d) H thng camera Bumblebee.

Cht lng ca cc bn khc bit c

biu din nh l t l phn trm ca cc im

nh vi cc li sai lch ny (pixel c s ph

hp xu) [6]:

(9-18)

trong X * Y i din cho kch thc ca

hnh nh, dC l bn chnh lch tnh ca hnh

nh th nghim v dT l bn chnh lch s

tht. S tht chnh lch bn mt t l

nghch o ca khong cch tht mt t.

Phng trnh (9-19) cho thy lm th no

tnh ton bn chnh lch s tht mt t t

bn

(9-19)

vi DT l s tht bn su mt t, h l

chiu cao t mt phng t, DT * h l khong

cch tht mt t, B l c s gia cc my nh,

IRES c phn gii hnh nh v f l tiu c.

a) b) c) d)


46

Bng 1. So snh kt qu ca cc gii thut tnh bn chnh lch

nh kim tra

SAD

thng

thng

SAD

phn

vng lai

H thng camera

Bumblelee

Quyn sch

9,64% 4,12% 3,59%

Ci vt 8,48% 4,72% 3,83%

Rubic 9,26% 4,37% 3,51%

Ta nh 9,91% 4,21% 3,65%

Cc bn chnh lch thu c t vic

xut lai phn on da trn thut ton SAD

phn vng lai c so snh vi cc phng

php khc (s dng h thng camera

Bumblebee v phng php SAD m khng

phn on). Trong ( bng 1), s khc bit gia

t l phn trm im nh li chnh lch c

trnh by. Nh c th thy trong (hnh 28), cc

thut ton SAD phn vng lai to ra kt qu

chnh xc hn so vi thut ton SAD m khng

phn on. Ngoi ra, hiu sut ca phng

php l gn t n hiu sut ca h thng

camera Bumblebee.

Cui cng, cc thut ton phn on lai

tn dng c li th nhanh chng ca thut

ton Mean Shift v chnh xc t thut ton

Belief Propagation. Li th ln ca mt thut

ton SAD lai l bt k phn on u c pht

hin c nhn dng t ng. Thut ton ny

t c mt hiu sut phn on gn thi

gian thc v kt qu chnh xc cao.

10. Kt lun:

Bi vit nghin cu so snh cho vic khi

phc bn su da trn cc thut ton phn

vng lai c xut s dng qu trnh lc.

Cc thut ton c th nghim trn thc t

vi cnh phc tp v tnh trng nh sng km

da trn h thng camera stereo cng nghip t

Bumblebee, t kt qu th nghim ta c th tm

mt bn chnh lch, m dch chuyn chnh

lch gia hai hnh nh v cui cng l c s

dng c tnh gi tr chiu su. Da trn cc

thut ton tng bnh phng khc bit (SSD)

v tng s khc bit tuyt i (SAD) c th tm

thy bn su trc tip. Ty thuc vo cc

k thut ph hp da trn cc thut ton SAD

v SSD mt nguyn tc gia thi gian chy v

cht lng cn phi c la chn. Cui cng,

thut ton SAD ph hp hnh nh stereo c

la chn thc hin cc th nghim tip theo,

bi v cc thut ton SSD i hi gn nh tng

gp i thi gian. Kt qu th nghim c

trnh by trong (Hnh 28) cho thy thut ton

SAD phn vng lai cho kt qu tt hn hn

thut ton SAD m khng cn s dng pjaan

vng v SAD iu chnh nhng hi km hn so

vi my nh ni ca h thng Bumblebee. Cc

thut ton SAD phn vng lai c xut

cng cho thy hiu sut cao hn. Trong tng

lai, ti d nh thc hin nghin cu v cng

kim tra cc thut ton phc tp hn.

Ti liu tham kho:

[1] Dorit Borrmann, Jan Elseberg, Kai Lingemann, Andreas Nchter (2011), The 3D Hough transform for plane detection in point clouds: A

Review and a new Accumulator Design, Received: 13 January 2011 / Revised: 13 February

2011 / Accepted: 10 March 2011, 3D Research

Center and Springer 2011

[2] Yedida, J. S, Freeeman, W. T, Weiss, Y. Understanding belief propagation and it is

genneralizstions. Exploring Artificial Intellrgence

in the New Millennium, 2003, Chap.8, p, 236 239.

[3] POINT GREY, Bumblebee Stereo Vision Camera Sytems. BB2 08S2 (datasheet). 2 pages. [Online] Cited 2011-10-23. Advailable at:

http://www.ptgrey.com/products/bumblebee2_xb3

_datasheet.pdf

[4] Scharstein, D, Szeliski,R, A taxonomy and evaluation of dense two frame stereo


correspondence algorithms. International Jounrnal

of Computer Vision, 2003, vol, 47, no. (1/2/3),

p.& - 42

[5] Brown, M, Z, Burschka, D, Hager, G, D, Bhartia, P. Advances in computional stereo. IEEE

Transactions on Pattenrn Analysis and Machine

Itelligence, 2003, vol, 25, no.8.

[6] KUHL, A. Comparison of stereo matching algorithms for mobile robots. Centre for

Intelligent Information Processing Sytem 2005,

University of Western Australia, p. 4 24.

[7] Cao, X., Foroosh, H, H. Camera calibration using symmetric objects. Image Processing IEEE

Transactions, 2006, vol, 15, no. 11, p.3614 3619.

[8] Shimizu, M., Okutomi, M, Calibration and rectification for reflection stereo. In IEEE

Conference on Computer Vision and Pattern

Recognition CVPR Anchorage ( USA), 2008, p.1

8.

[9] Hartley, R, Zisserman, A, Multiple View Geometry in Computer Vision 2

nd ed. Cambridge:

University Press, 2005.

[10] Zhang, Y. J. Advance in Image and Video Segmentation. 1nd ed. USA: IRM Press, 2006.

[11] Wang, G, JU, H, A disparity map extraction algorithm for lunar rover BH 2. In IEEE

International Conference on Intelligent

Computing and Intelligent Sytems ICIS 2009.

Shanghai, 2009, vol. 4, p. 385 389.

[12] Mckinnon, B., Baltes, J. Practical region based matching for stereo vision. In IWCIA, 2005, vol.

3322 of Lecture Notes in Computer Science,

Springer, p. 726 738.

[13] Craig Watman, Fast Sum of Absolute Differences Visual Landmark Detector, Robotic Systems Laboratory Department of Systems

Engineering, RSISE, Australian National

University, Canberra, ACT 0200 Australia, Email:

[email protected]

[14] Christor Georgoulas, Georgios CH, Real-time stereo vision applicasions.Laboratory of

Electronics,Democritris University of Thrace

Xanthi, Greece p.267-292.

[15] Guan, S, Klette, R, Belief Propagation on edge image sequences. InmProceedingx Robot Vision

LNCS 4931, 2006, p. 291 302.

[16] Siqiang, L., Wei, L, Image segmentation basedon the Mean Shift in the HSV space. In 26

th

Chinese Control Conference, 2007. [Online], p.

476 479.

[17] Benco, M., Hudec, R, The advances image segmentation techniques for broadly useful

retrieval in large image database. In NSSS IX,

Tatranske Zruby (Slovakia), 2006, p. 40 44.

[18] He, R, Zhu, Y. A hybrid image segmentation approach based on Mean Shift and fuzzy C Means. In Asia Pacific Conference on Information

Processing. [Online], 2009.

[19] Comaniciu, D., Meer, P. Mean Shift: A robust approach toward feature space analysis IEEE

Transaction on Pattern Analysis and Machine

Intel., 2002, vol. 24, no. 5, p. 1 18.

[20] Rodriguez, R., Suarez, A. G. An image segmentation algorithm using interatively the

Mean Shift. Progress in Pattern Recognition,

Image Analysis and Appliscations. 2006, LNCS

4225, Berlin Heidelberg: Springer, vol.

4225/2006, p. 326 335.

[21] Hudec, R. Adaptive Order statistics L filters, 1

st ed. University of Zilina: EDIS Press, 155

pages, ISBN 978 80 554 0248 2, 2011 (in Slovak).

[22] Rostam Affendi Hamzah, Hasrul Nisham Rosly, An Obstacle Detection and Avoidance of A Mobile Robot with Stereo Vision Camera , Faculty of Electronics & Computer Engineering,

UTeM, Malaysia. [email protected]


48

Comparative Study of Image Processing Algorithms Calculate

Depth Stereo Image Camera Applications in the Visual System

Bch Ngc Minh

Centre Development Vietnam National University, Hanoi, 144 Xun Thy, Hanoi, Vietnam

Abstract: There are three basic methods to compare the similarity between two images, which is

SAD, SSD and NCC. NCC method is using cross- correlation between the pixels so the calculations

are complex . These include the arithmetic average, total, multiplication total, square root should this

method definitely perform very time consuming. Both SAD method and SSD method doesnt much

difference the complexity of the algorithm so we need to do an experiment to verify the quality of the

depth maps and the speed of execution. From the results that we choose a more appropriate method

Comparison of running time between SAD and SSD algorithms show that the choice of the SAD

algorithm is more reasonable, because the SSD algorithm needs nearly twice the time to run. SAD

method can solve the problem of finding depth in 3D images. A point in space to acquire images of

two lenses in two different locations. Therefore so before finding the depth of the pixel, we need to

find the corresponding pixels. SAD method is the easiest method to find the pixel .

SAD method has many calculate ways, calculate by traditional methods SAD, adjustment SAD

method (based on the image border) , segmentation SAD method (image segmentation). In Here we

choose between two methods of adjustment SAD method and segment SAD method decreased 20 %

compared with traditional SAD.

Then we consider the hybrid algorithm SAD partition is created by the combination to two

techniques: Belief Propagation and the Mean Shift segmentation algorithm. This approach combines

the advantages of both methods segment. Mean Shift algorithm is fast results and Belief Propagation

perform very accurate segmentation.

Keywords: Image segmentation, Belief Propagation, Mean Shift, SAD, 3D image.

Documents

Nghiên cứu so sánh các thuật toán xử lý ảnh tính độ sâu ảnh stereo ứng dụng trong hệ thống camera thị giác