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1、ᜧắ ᦻ᤺⌕ᨬLhe℉ឋᱯ©îᵨüý⊤☢，b e℉ឋᱯ©Ḅüý⊤☢◍g4，Ïl,Éüý⊤☢Ḅᐰ¢º¢»e℉ឋᱯ©，;Gaborÿᱯ©@Aᔠ，Ç]âª◍IJ，ᨵᑭEF¿。ÏlqAÔ⊤，e℉ឋᱯ©Ḅüý⊤☢◍g4᳛，ឋ:,ᓣe，ᐹᨵãḄq▭îᵨst。ᐵ ： ℉ឋᱯ!，#$⊤☢'◍)*，+,-.，ᱯ!/ᔠ， ℉ឋᱯ!12úIV⚓万方数据ᜧắ ᦻABSTRACTTheBasedonImprovedImageSaliencyCharacter
2、isticDetectionBilletSurfaceDefectDetectingTechnologyABSTRACTWiththecontinuousdevelopmentofcomputervisiontechnology,industry-orientedvisualdefectdetectiontechnologyhasattractedmoreandmoreextensiveattentionincreasingly.However,astheproductiontechnology’srapid
3、ascension,manytraditionaltechnologieshavebeenunabletomeettherequirementsofindustrialproduction.Ifthedefectdetectiontechnologycansimulatethewayofvisionsystemworking,whichprioritizedlocatingsuspecteddefectareasandthencentralizedprocessingwhichcanavoidcomputin
4、gresourceswasteandimprovedetectionaccuracy.Therefore,howtodesignthevisualdefectdetectionprocessthatconformstothesaliencyfeaturesofvisualattentionhasanimportantpracticalvalue.Firstofall,thisthesiselaboratesthecomposition,attentionmechanismandformingprocessof
5、thehumanvisualsystem.Thenthethesisintroducestheexistingclassicalsaliencymodelindetail,includingthebasedonbiologicalvisionIttimodel,thebasedonfrequencydomainfastprocessingHoumodel,thebasedoncontext-awareGofermanmodelandthebasedonimagesegmentationandareacontr
6、astChengmodel.Thesemodels,however,alsohavelimitations:lowefficiency,featureinformationsimplificationandpoorrobustnesstocomplexbackgroundandsoon.Synthesizedtherequirementsofvisualdefectdetection,thisthesispresentsanovelsaliencyalgorithmbasedonthefusionofglob
7、alchromaticdifferenceandlocallow-levelfeature.Simulatedthevisualsystemmechanism,themethodcalculatesthecolorsaliencyinnaturesceneimagetogettheglobalsaliencyfeaturemapatfirst,whichcombinesthehistogramquantizationandsaliencysmoothing;thenextractavarietyoflow-l
8、evelfeatures,makethemfusiononmulti-scalefordifferentfeaturesandgetfinallocalsaliencymapinlinearweightedsynthesisway;Finallythroughthefusionofglobalandlocalfeaturesandúv⚓万方数据ᜧắ ᦻABSTRACTthestrateg
