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基于等周理论的自动多级阈值分割方法(英文).docx

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基于等周理论的自动多级阈值分割方法(英文) Title:AutomatedMultilevelThresholdingSegmentationMethodbasedonOtsu'sTheory Abstract: Imagesegmentationplaysacrucialroleinnumerouscomputervisiontasks,suchasobjectdetection,imagerecognition,andmedicalimageanalysis.Theprocessinvolvesdividinganimageintoseveraldistinctregions,whichsimplifiessubsequentanalysisandextractionofvaluableinformation.Multilevelthresholdingsegmentationmethodshavegainedpopularityduetotheirabilitytohandlereal-worldimageswithcomplexbackgroundsandvaryingintensitylevels.Thispaperproposesanautomatedmultilevelthresholdingsegmentationmethodbasedonthewell-knownOtsu'stheory. Introduction: Imagesegmentationconsistsofdividinganimageintomultipleregions,inwhichpixelssharesimilarcharacteristics.Multilevelthresholding,apopularapproachtoimagesegmentation,aimstodivideanimageintomorethantworegionsbasedonmultiplethresholdvalues,asopposedtotraditionalbinarysegmentationmethods.Inthisstudy,weproposeanautomatedmultilevelthresholdingsegmentationmethod,whichutilizesOtsu'stheoryasafoundation. Otsu'sTheory: Otsu'stheory,originallyproposedbyNobuyukiOtsuin1979,isawidelyusedautomaticthresholdselectionmethod.Itmaximizesthebetween-classvarianceofanimagetodetermineanoptimalthresholdvalueforbinarysegmentation.However,applyingOtsu'smethoddirectlytomultilevelthresholdingcanbechallengingduetotheincreasedcomplexity.Thus,ourmethodaimstoextendOtsu'stheoryformultilevelthresholdingsegmentation. Methodology: 1.Preprocessing:Theinputimageundergoespreprocessingstepssuchasnoiseremoval,contrastenhancement,andnormalizationtoensureaccuratesegmentationresults. 2.HistogramCalculation:Thehistogramofthepreprocessedimageiscomputedtoobtainstatisticalinformationabouttheintensitydistribution. 3.ThresholdInitialization:Initialthresholdvaluesaresetbasedontheintensityhistogram. 4.IterativeThresholdRefinement:ThethresholdvaluesarerefinediterativelyusingtheprinciplesofOtsu'stheory.Ateachiteration,theregionvariancesarecalculated,andthethresholdvaluesareupdatedtomaximizethebetween-classva