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1、ElasticimagematchingAbstractOnefundamentalprobleminimagerecognitionistoestablishtheresemblanceoftwoimages.Thiscanbedonebysearchingthebestpixeltopixelmappingtakingintoaccountmonotonicityandcontinuityconstraints.WeshowthatthisproblemisNP-completebyreductionfrom3-SAT,thusgivingevidencethattheknow
2、nexponentialtimealgorithmsarejustified,butapproximationalgorithmsorsimplificationsarenecessary.Keywords:Elasticimagematching;Two-dimensionalwarping;NP-completeness1.IntroductionInimagerecognition,acommonproblemistomatchtwogivenimages,e.g.whencomparinganobservedimagetogivenreferences.Inthatpro-
3、cess,elasticimagematching,two-dimensional(2D-)warping(UchidaandSakoe,1998)orsimilartypesofinvariantmethods(Keysersetal.,2000)canbeused.Forthispurpose,wecandefinecostfunctionsdependingonthedistortionintroducedinthematchingandsearchforthebestmatchingwithrespecttoagivencostfunction.Inthispaper,we
4、showthatitisanalgorithmicallyhardproblemtodecidewhetheramatchingbetweentwoimagesexistswithcostsbelowagiventhreshold.WeshowthattheproblemimagematchingisNP-completebymeansofareductionfrom3-SAT,whichisacommonmethodofdemonstratingaproblemtobeintrinsicallyhard(GareyandJohnson,1979).Thisresultshowst
5、heinherentcomputationaldifficultiesinthistypeofimagecomparison,whileinterestinglythesameproblemissolvablefor1Dsequencesinpolynomialtime,e.g.thedynamictimewarpingprobleminspeechrecognition(seee.g.Neyetal.,1992).Thishasthefollowingimplications:researcherswhoareinterestedinanexactsolutiontothispr
6、oblemcannothopetofindapolynomialtimealgorithm,unlessP=NP.Furthermore,onecanconcludethatexponentialtimealgorithmsaspresentedandextendedbyUchidaandSakoe(1998,1999a,b,2000a,b)maybejustifiedforsomeimagematchingapplications.Ontheotherhandthisshowsthatthoseinterestedinfasteralgorithms––e.g.forpatter
7、nrecognitionpurposes––arerightinsearchingforsub-optimalsolutions.Onemethodtodothisistherestrictiontolocaloptimizationsorlinearapproximationsofglobaltransformationsaspresentedin(Keysersetal.,2000).Anotherpossibilityistouseheuristicapproa