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1. Tracking and Guiding Multiple Laser Beams for
Beam and Target Alignment
1 Introduction
In orderto applythe theoriesof inertial confinementfusion(ICF) topractice,the challengesassociated
withbeam
and targetalignmentsystemmustbe overcome[1].Itisnecessarytotake measurestorealize rapidand
precise alignmentinatime as shortas possible.Inordertoachieve
highershootingaccuracy,the laserspotsshouldbe guided
throughcontinuousvisual feedbackinreal-time[2].Normally,the processof aligningmultiple laser
beamsto the
Laser Beam Targeting System
desiredregiononthe targetiscalleda beamandtarget
alignmentprocess,andasensorforaligningmultiple laser
beamsto the target iscalleda targetalignmentsensor,
whichmainlyconsistsof the conjugate reflectivitymirror
and the microscope lens,asshowninFig.1. In thiswork,
3 dedicatedlaseralignmentdevices are integratedtoguide
3 laserbeamstoachieve the beamandtarget alignment.
For eachlaserbeam,the laserfrom the transmitterisamplified,processedthroughafilterwheel,
focusedbya set
of convergentlenses,andthenfilteredviaanaperture of a
circularhole of 6 mm diameter.Finally,the laserisfocused
againby a convex lensandisreflectedtothe endsurface of

2. Laser Beam Targeting System
target bya high-reflectivity mirror.Therefore,the detecting,trackingandguidingtechnologiesof laser
spotsbecome
veryimportantsothat multiple laserbeamscanshootthe
desiredregionof the targetinthe beamand targetalignmentprocedure.
RegularPaper
ManuscriptreceivedDecember25,2013; acceptedDecember4, 2014
RecommendedbyAssociateEditorNazimMir-Nasiri
Thiswork wassupportedbyNational Natural Science Foundation
of China(Nos.61227804 and61105036).
c Institute of Automation,ChineseAcademyof Science and
Springer-VerlagBerlinHeidelberg2015
The detectionandsegmentationof multiple spotsinimage sequencesisafundamental stepbefore the
trackingor
whenthe trackingisfailed.The laserspotisassumedtobe
the onlypart of the image witha highlightintensity.The
commonapproach isto extractthe spotsbybackground
subtraction.However,inpractice,the intensityof laser
may randomlychange,the illuminationinthe scene may
not be verystable andeventhe intensityof acylindrical
target mayvibrate slightly.All of these mayinduce the
changesof background.StaufferandGrimsor[3] modeled
each pixel asamixture of Gaussiansandusedan on-line
approximationtoupdate the model.However,the method

3. suffersfromslowlearningatthe beginningandisnotsensitivetothe small motions.Animproved
Gaussianmixture
model waspresentedbyZivkovic[4],inwhichnotonlythe
parametersbutalsothe numberof componentsof the mixture were constantlyselectedforeachpixel.
However,this
methodhashighcomputational cost,especially,inthe face
of the highimage resolution.
The tracking algorithmcanprovide the positionfeedbackforthe spotinreal-time.In[5],the object
tracking
was dividedintopointtracking,kernel trackingandsilhouette tracking.Features,suchascolor,edges,
optical flow
and texture are oftenchosenfortracking.Theycan be representedbyaprobabilisticmodelandthen
detectedinconsecutiveframes.Ingeneral,the mostdesirable featuresof
spotare the oneswhichcan be usedtodistinguishone spot
fromthe others.Consideringthe grayimage,the biggest
difference betweendifferentspotsisthe contourthenthe
intensity.Moreover,due tothe factthat the spot isnon
Laser Beam Targeting System
The detectionandsegmentationof multiple spotsinimage sequencesisafundamental stepbefore the
trackingor whenthe trackingis failed.The laserspotisassumedtobe the onlypart of the image witha
highlightintensity.The commonapproachisto extractthe spotsby backgroundsubtraction.However,
inpractice,the intensityof lasermayrandomlychange,the illuminationinthe scene maynotbe very
stable andeventhe intensityof acylindrical targetmayvibrate slightly.All of these mayinduce the
changesof background.StaufferandGrimsor[3] modeledeachpixel asamixture of Gaussiansandused
an on-line approximationtoupdate the model.However,the methodsuffersfromslow learningatthe
beginningandisnotsensitivetothe small motions.AnimprovedGaussianmixture model was
presentedbyZivkovic[4],inwhichnotonlythe parametersbutalsothe numberof componentsof the
mixture were constantlyselectedforeachpixel.However,thismethodhashighcomputational cost,
especially,in the face of the highimage resolution.

4. The tracking algorithmcanprovide the positionfeedbackforthe spotinreal-time.In[5],the object
trackingwas dividedintopointtracking,kerneltrackingandsilhouette tracking.Features,suchascolor,
edges,optical flowandtexture are oftenchosenfortracking.Theycanbe representedbyaprobabilistic
model andthendetectedinconsecutive frames.Ingeneral,the mostdesirable featuresof spotare the
oneswhichcan be usedto distinguishone spotfrom the others.Consideringthe grayimage,the biggest
difference betweendifferentspotsisthe contourthenthe intensity.Moreover,due tothe factthat the
spotis non-rigid,the trackingalgorithmbasedonitscontourismore practical.Many contourmodels
have beenreportedfortrackinginthe previousliterature,suchasoptical flow,level set,snakes,
balloonsandactive contoursmodel[6–8].Some contourtrackingmethodsbasedonboundarycodes
were investigatedin[9,10].However,theyare limitedtothe boundary-basedinformationandare
sensitivetonoise.Inordertoovercome the drawbacksof the sensitivenesstonoise andpoorimage
contrast,a particle filteringalgorithmforgeometricactive contourstrackingwasproposedin[11].
However,these techniquesrequire anumberof iterationsandare computationallytooexpensivefor
real-time applicationonmultiple spotstracking.Itisnecessarytodevelopone rapidandrobustcontour
trackingscheme forspots.
Laser Beam Targeting System
Anotherimportantproblemisthatthe spotsmaymix togetherandinterfere witheachotherwhen
multiple laserbeamssimultaneouslyshootthe target.The problemmaybe solvedbyguidingasingle
beamat a time,however,whichistime-consuming.Therefore,occlusionhandlingisadifficultissue in
the face of multiple spotstracking.Inthe previousliterature,the appearancemodel wasincorporated,
or the target wastreatedas a blobwhichmaymerge andsplit,or an exclusionprinciple wasemployed
by usingthe jointprobabilisticdataassociationfilterandthe particle filterwasemployedtoavoidthe
highcomputational load[12–15].The priorinformationof shape isoftenintegratedintocontour
representation.Yilmazetal.[16] proposedanon-rigidtrackingmethod,whichwasachievedbyevolving
the contour fromframe to frame withsome energyfunctions.The contourrepresentedbylevel setswas
usedto recoverthe missingobjectregionsduring occlusion.However,these methodsrequire precise
model,increase the computational complexityandmayfail inthe face of the rapidmotions.
The recognitionof multiplespotsisalsoakeyproblemduringmultiple spotstracking.Inorderto
distinguish differentspots,shape representationandmatchingtechniquesshouldbe considered.A
numberof successful shape matchingalgorithmswere proposed.One of the mostpopularmethodsisto
use Hausdorff distance,althoughitisverysensitivetooutliers.Somemethodscompare shape bythe
feature vectorwhichcontainsthe descriptorssuchasarea,geometricmoments,shape matrix,
appearance viagray histograms,optical flow vectors,etc.[17],while othersdirectlydowiththe aidof
pixel brightness[18].Belonggieetal.[19] proposedthe shape contextforshape matchingandobject
recognition,whichdescribedthe contourpointsbyhistograminthe log-polarspace.The similarity
betweentwoshapeswascomputedbyasumof matchingerrorsbetweencorrespondingpoints.

5. However,alarge amountof calculationswillbe neededandtheyare hardto satisfythe real-time
requirement.
Laser Beam Targeting System
The motivationof thispaperisto developthe detection,trackingandguidingschemesformultiple laser
spotsbasedon a beamand targetalignmentexperimentalplatform.Anaccurate andreal-time system
for multiplelaserbeamsshootingispresented,whichconsistsof spotssegmentation, spotscontour
trackingevenunderocclusionandspotsguidingbasedonvisual feedbackcontrol.
The rest of thispaper isorganizedasfollows.Section2describesmultiplespotsdetectionandtracking
strategy,inwhichthe spotsegmentation,the contour trackingandthe shape matchingalgorithmsare
introduced.Inordertoaccomplishthe beamand targetalignmenttask,Section3presentsmultiple
spotsguidingscheme.Section4providesthe experimental configurationandthe analysisof experiment
results.Finally,the paperisconcludedinSection5.
2 Multiple spotsdetectionandtrackingstrategy
The achievementof the beamandtargetalignmentbasedonvisual feedbackneedstoobtainthe
positionsof multiple spotsinreal-time.The accurate positionsneedtobe determinedbythe detection
and trackingstages.AsshowninFig.2, the proposedstrategyisinitializedwithastatusflagL = 1. Each
spotis recognizedbyitsshape andisnumberedafterthe detection.Meanwhile,itslocation,width,
height,image momentsandsoonare alsocalculated.If all spotsare found,thenflagL is setto 0. When
a newimage iscaptured,the trackingalgorithmisemployedtoobtainthe new featuresof spots.When
occlusionoccurs,the trackingscheme combinedwith apredictionmechanismwill determinethe new
positionsof spots.If the shape matchingbetweenthe currentcontourandthe previousone isfailed,
then,flagL changesto 0. Otherwise,the positionsof the currentspotswill be providedtothe guiding
stage.Then,the spotsin the nextframe will be trackeduntil stopping.
3 Spotsdetectionstage
3.1 Spotsdetectionstage
Firstof all,the movingspotsare segmentedfromthe beamandtargetimages.However,noise maybe
introducedandthe differentialimage maybe incomplete bystationarybackgroundsubtraction.Many
solutionsinthe previousliterature have beenproposedforreal-time foregrounddetectionfrommoving
background.Here,the adaptive Gaussianmixturemodel(GMM) isemployedtoobtainthe spots
background[20].A Bayesdecisionrule forclassifyingbackgroundandforegroundisformulatedandthe

6. learningstrategyisintroducedtoadaptto slightchangesinbackground.The probabilityof eachpixel
value at time tcan be writtenby
p(xt)=∑i=1Kwiη(xt,μi,Qi)
(1)
where Kis the numberof Gaussiandistributions,ωi is the weightof the i-thGaussiancomponent,μi is
the meanvalue,Q i is the covariance matrix andη(x t , μ i , Q i ) isthe i-thGaussianprobabilitydensity
function,whichisrepresentedby
η(xt,μi,Qi)=1(2π)D2|Qi|12e−12(xt−μi)TQ−1i(xt−μi).
(2)
In orderto avoidthe complex matrix computation,letQi=σ2iI.Consideringthe highresolutionof the
spotimage,nomore than3 Gaussianmodelsare initialized.
Each pixel isfirstlyclassifiedaseitherbackgroundoraforegroundpixel bythe models.The K
distributionsare orderedbasedonthe fitnessvalueωi /σ i . The firstB distributionsare selectedasa
model of the background,whichare estimatedby
B=argminb(∑i=1bwi>T)
(3)
where T isthe thresholdof backgroundweightvalue.The Gaussianmodel thatmatchesthe current
pixel value will be updatedbythe followingformulae.
w^t+1i=w^ti+α(1−w^ti)μ^t+1i=μ^ti+α(xt+1−μ^ti)Q^t+1i=Q^ti+α((xt+1−μ^t+1i)(xt+1−μt+1i)T−Q^ti).
(4)
If no Gaussianmodel matchesthe currentpixel value,thenthe leastprobablemodelisreplacedbythe
formulae wt+1i=α,μt+1i=xtandQt+1i=σ0. If the maximumnumberof componentsisreached,the
componentwiththe smallestweightwill be discarded.

7. However,the foregroundregionsegmentedbythe Gaussianmixture model isnotsufficienttobe clear.
Firstly,abinaryimage isobtainedthroughadaptive thresholdsegmentation,inwhichthe value of each
pixel iscomparedwiththe weightedaveragevalue aroundthe pixel.
((5))
where Ib¯(u,v) isthe convolutionof pixelbyone Gaussiankernel operatorandI T isthe constantvalue.
Then,the region-basednoise cleaningisapplied,suchasthe morphological openoperationincluding
the erosionbythe structuringelementA thenthe dilationbythe structuringelementB,denotedby
(X⊕A)⊖B.
(6)
Thisopeningoperationcangenerallyremoveverysmall regions,eliminatethinprotrusionsandsmooth
the contour of the spot. Then,the shape filterisusedtoclassifythe spots.Sofar,all spotsare numbered
and eachone has its ownID number.
3.2 Spotstrackingstage
In thissubsection,the contourtrackingalgorithmbasedonthe chaincode isintroduced.Many
applicationsusingchaincode representationhave beenreported inpreviousliteratures.The first
approach forrepresentingthe arbitrarygeometriccurve usingchaincode wasproposedby
Freeman[21].Inthisapproach,an arbitrarycontour can be representedbyasequence of small vectors
of unitlengthanda setof possible directions.There are twostandardcode definitionsusedtorepresent
contour,includingthe crackcode basedon4-connectivityandthe chaincode basedon8-connectivity.
In thiswork,the real-time androbustnessare veryimportantformultiplespotstracking.Here,the 8-
connectivitychaincode isemployedforrepresentingthe contourof spot,whichisbasedonthe
connectivityof neighboringpixels[22].Fig.3illustratesthe changesof 8possible absolute directions,
whichare indicatedbynumbers.“0”indicatesthe directionchange tothe east,“1” indicatesthe
directionchange tothe northeast,“2” indicatesthe directionchange tothe north,“3” indicatesthe
directionchange tothe northwest,“4” indicatesthe directionchange tothe west, “5” indicatesthe
directionchange tothe southwest,“6”indicatesthe directionchange tothe southand“7” indicatesthe
directionchange tothe southeast.A change betweentwoconsecutive chaincodesmeansachange in
the directionof the contour.Thus, each spot’scontourcan be codedbythe chaincode in the image
space.

8. Generally,the basicprinciple of the trackingbasedonchaincode of 8 directionsistoseparatelyencode
each connectcomponent.Itcan be dividedinto3stepsas follows.
Firstly, the initial centerof the trackedspotshouldbe specifiedsothatthe firstborderpixel canbe
found.The initial positioncanbe obtainedfromthe detectionprocedure.Startingfromthe firstcenter,
the firstborderpixel canbe detectedalongthe U-axisdirection.Inordertosearch a new contourin a
small regionof interest(ROI) whenthe trackingisfailed,one suitable searchwindow isset.A copyof
the current spotshouldbe createdinorderto determine whetherthe currentspotissimilartothe next
one.If no similarspotisdetected,thiscopyissetto the currentspot.
Secondly,the nextborderpixel isconsideredbyupdatingthe pixel coordinatesalongthe 8directions.
The coordinate transformationrulesare describedas
Laser Beam Targeting System