基于自相關(guān)算法的顯微圖像粒度分析及實現(xiàn)研究(1)

1、碩士學位論文壘!坐型—————————————————————————————一AbstractGrainsizedistributionisanimportantindicatoroftheparticlesAnaccurateresultof虹ainsizediStribu60nplaysanimportantroleinwaterconservancyproject，sucnaSreseⅣoirs，ports，waterwaysa

2、ndSOonTraditionalmethodhasmanyshotcomings上Iorexample，notonlydoesthemethodneedtotakeplentyoftimetoh趾dlecomplexcalculationbutalsoitsresultshasgreatsubjectiveinfluence，whichCannotmeetpeople’sneedTh幽re，thecuHenturgentproblem

3、ishowtoobtainthegrain。sizedistributlonoftheparticlesWithmerapiddevelopmentofcomputerimageprocessingtechnology姐dmicroscopicimageacquisitiontechnologyapplicationofmicroscopic1mageprocessingtechn0109yinthefieldofparticlemea

4、surementhasreceivedwidespreadartentlonFirstly，thepaperintroducestheresearchStatusofparticlemeasurementtechnologyThroughthestudyofparticlemeasurementmethods，themicroscopicimagepro∞s她basedonautocorrelationalgorithmispropos

5、ed，anewautocorrelationmicroscopicimageprocessingsystembasedonenlbeddedARMplatformisdesignedInaddition，theworkingprincipleofparticlemeasuringsystemandtheautocorrelationalgorithm1sdlscussedComparingwithtraditionalmethod，th

6、ismethodCanimprovetheprocesslngspeedwlmoutsacrificingtheaccuracyoftraditionalmethodsSecondlytheembeddedL1nuxsYstemplatfo肌wasbuiltImageacquisitionandprocessingofgraphicaluserinterfaceapplicationsb2usedonQtwasdesignedTheap

7、plicationofautocorrelationalgorithminp砒cleslzemeasurementsystemwasrealizedFinallytheexperimentalresultsshowthatthedeslgnlsfeasibleandhasgoodpracticalvalueintheconditionofquickprocessxngspeedandlowcostTlleautOCOrrelationa

8、lgorithmsimplifiestheproceduresofparticlemeasurementaImimprovesthemeasurementefficiencywhichprovidesnewideasandresearChdlreCtlonsmthemeaslurementoftheparticlesKeyword：grainsizedistributi。n，autocorrelati。nalg。rithm，micros