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1、JournalofForestryResearch,17(1):57–61(2006)57ClassificationofwoodsurfacetexturebasedonGauss-MRFModelWANGKe-qi,BAIXue-bingNortheastForestryUniversity,Harbin150040,P.R.ChinaAbstract：ThebasaltheoryofGauss-MRFisexpoundedand2–5orderGauss-MRFmodelsareestablis
2、hed.Parametersofthe2–5orderGauss-MRFmodelsfor300woodsamples’surfacetexturearealsoestimatedbyusingLMS.Thedataanalysisshowsthat:1)differenttex-tureparametershaveaclearscattereddistribution,2)themaindirectionoftextureisthedirectionrepresentedbythemaximumpa
3、rameterofGauss-MRFparameters,and3)forthosesampleshavingthesamemaindirection,thefinerthetextureis,thegreaterthecorrespondingpa-rameteris,andthesmallertheotherparametersare;andthehighertheorderofGauss-MRFis,themoreclearlythetextureisdescribed.Ontheconditi
4、onofthesecondorderGauss-MRFmodel,parameterB1,B2oftangentialtexturearesmallerthanthatofradialtexture,whileB3andB4oftangentialtexturearegreaterthanthatofradialtexture.Accordingtothevalueofseparatedcriterion,theparameterofthefifthorderGauss-MRFisusedasfeat
5、urevectorforHammingneuralnetworkclassification.Asaresult,theratioofcorrectnessreaches88%.Keywords：Woodsurfacetexture;Gauss-MRF;Featureparameter;Parameterestimation,Separationjudgment;ClassificationClCnumber:S781.1Documentcode:AArticleID:1007-662X(2006)0
6、1-0057-05IntroductionGauss-MarkovRandomFieldThenaturaltexturehasacomplicatedstructure.PresentlyMarkovRandomField(abbreviatedasMRF)isthemathe-therehasnotbeenastandardtodescribeitsfeature.Howtode-maticstheoryofrandomprocessdescriptionputforwardbyD.scribea
7、ndclassifynaturaltexturesisanimportantissueintheGemanandS.Gemanin1984.Itsdefinitionisasfollows:fieldofcomputervision(LiandLiu1998).ThedescriptionofLetS=(S1,S2,…,SN)bethepositionsetina2Dspace,Xbetexturefeatureisdividedintostatisticalmethod,structuralther
8、andomvariable.Therandomevent(x1,x2,…,xN)canbemethod,andmodelmethod(Sheng2000)Ithasbeenprovedbyexpressedas（X=ω）,ω∈Ω，ΩisthevaluespaceofrandompracticethatthestatisticalmethodrepresentedbyGrayLevelvariable;ζistheneighborhoodsystemoft
