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1、Agent-BasedImageIrisSegmentationandMultipleViewsBoundaryRefiningRuggeroDonidaLabati,VincenzoPiuriFellow,IEEE,FabioScottiMember,IEEEAbstract—Thepaperpresentstwodifferentmethodstodealwiththeproblemofirissegmentation:anagent-basedmethodcapabletolocalizethecenterofthepupilandamet
2、hodtoprocesstheirisboundariesbyamultipleviewsapproach.Inthefirstmethod,anagentcorrespondstothecoordinatesofaspecificpointofanalysisintheinputimage.Apopulationofagentsisdeployedintheinputimage,then,eachagentcollectslocalinformationconcerningtheintensitypatternsvisibleinitsregio
3、nofinterest.Byiterations,anagentchangesitspositionaccordinglytothelocalproperties,movingtowardstheestimationofthepupilcenter.Ifnoavailableinformationispresentinitsregionofinterest,theagentwillmoveitselfFig.1.MultiAgentPupilLocalization.Startingfromaninitialspatialconfiguratio
4、n(left),agentssearchforthepupilcenterbyaniterativealongarandomwalk.Afterfewiterations,thepopulationapproach.Whenthestoppingcriterionisreached,theareawiththehighesttendstospreadandthenconcentrateintheinnerportionofconcentrationofagentsintheimage(right)estimatesthepupilcenter.
5、thepupil.Oncethecenterofthepupilhasbeenlocated,theinnerandouteririsboundariesarerefinedbyanapproachbasedonmultipleviewsanalysis.Thismethodstartswithasetofpointsthatcanbeconsideredasanapproximationofthepupilcenter.Foreachpoint,adetailedestimationoftheirisboundariesiscomputed,a
6、ndthefinaldescriptionoftheirisboundariesisobtainedbymergingalltheobtaineddescriptions.ThetwomethodsweretestedusingCASIAv.3andUBIRISv.2images.Experimentsshowthattheproposedapproachesarefeasible,alsoineyeimagestakeninnoisyornon-idealFig.2.MultipleViewsBoundaryRefining.Startingfr
7、omasetofobservationpointsinsidethepupil(redcirclesintheleftsubplot),theinnerconditions,achievingatotalerrorsegmentationaccuracyuptoandouteririsboundaryarereconstructedbyprocessingtheradialgradient97%.transitionsforeachobservationpoint(coloredcurvesinthecentersubplot).Thediff
8、erentboundariesarefusedinordertoestimatetheirisedges(right).I.INTRODUCTIONT