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改进的基于灰度级的模糊C均值图像分割算法.docx

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改进的基于灰度级的模糊C均值图像分割算法 Abstract Imagesegmentationisoneofthemostessentialandwidelyusedtechniquesinimageprocessing.FuzzyC-means(FCM)algorithmisawell-knownmethodforimagesegmentation,whichworkseffectivelyinclusteringthepixelsofanimage.However,theconventionalFCMalgorithmsuffersfromsomelimitationssuchassensitivitytonoiseandinitialseedvalues,aswellastheinabilitytoconsiderthespatialcorrelationbetweenpixels.Toovercometheselimitations,severalmodificationshavebeenproposedinliterature.Inthispaper,anewmodifiedFCMalgorithmbasedongraylevelisproposed,whichtakesintoaccountthespatialinformationofpixels.TheexperimentalresultsdemonstratethattheproposedalgorithmoutperformstheconventionalFCMandotherstate-of-the-artalgorithmsintermsofsegmentationaccuracyandrobustness. Keywords:Imagesegmentation,FuzzyC-means,Graylevel,Spatialinformation,Segmentationaccuracy,Robustness. Introduction Imagesegmentationisafundamentalandcrucialprocessinimageprocessing,whichinvolvespartitioninganimageintomultipleregionsorsegmentswithsimilarcharacteristicsorproperties.Theapplicationsofimagesegmentationarediverseandwidespread,includingobjectrecognition,patternrecognition,computervision,medicaldiagnosis,andmanyothers.Imagesegmentationisachallengingtaskduetothecomplexityanddiversityoftheimages,whichrequiresrobustandefficientalgorithmstoachieveaccurateandreliableresults. FuzzyC-means(FCM)algorithmisawidelyusedclusteringalgorithmforimagesegmentation,whichhasbeenprovedtobeeffectiveinvariousapplications.However,theconventionalFCMalgorithmhassomelimitationsthataffectitsperformanceandapplicability.Firstly,thealgorithmissensitivetonoise,whichcanleadtomisclassificationofpixelsanddegradethesegmentationaccuracy.Secondly,thealgorithmissensitivetoseedvalues,whichcanleadtodifferentresultsfordifferentinitializations.Thirdly,thealgorithmignoresthespatialinformationofpixels,whichcanleadtoover-segmentationorunder-segmentationoftheimage. Toovercometheselimitations,severalmodifiedFCMalgorithmshavebeenproposedinliterature.Someofthesemodi