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基于二维直方图的otsu图像分割算法改进.docx

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基于二维直方图的otsu图像分割算法改进 Introduction Imagesegmentationistheprocessofdividinganimageintomultiplepartswiththeaimofextractingmeaningfulinformationfromtheimage.Itisafundamentaltaskincomputervisionandimageprocessing.TheOtsualgorithmisawell-knownandwidelyusedimagesegmentationalgorithmbasedontheconceptofthresholding.TheOtsualgorithmmaximizesthebetween-classvarianceofthegrayscaleintensities,andthenusesthethresholdtoseparatetheforegroundandbackgroundoftheimage.However,thisalgorithmhassomelimitations,suchasitssensitivitytonoiseandthedifficultyinselectionoftheoptimalthreshold.Inthispaper,weproposeanimprovedOtsuimagesegmentationalgorithmbasedonthetwo-dimensionalhistogram,whichcanovercometheselimitationsandimprovethesegmentationaccuracy. OtsuAlgorithm TheOtsualgorithmisawidelyusedimagesegmentationalgorithmbasedonthethresholdingofanimage.Thealgorithmassumesthattheimagecanbesegmentedintotwoclasses:foregroundandbackground.Thegrayscalevalueofeachpixelintheimageisusedasafeature,andthealgorithmdeterminesanoptimalthresholdthatmaximizesthebetween-classvarianceofthegrayscaleintensities.Theaimistofindathresholdtthatminimizesthewithin-classvarianceandmaximizesthebetween-classvariance.TheOtsumethodcanthusbesummarizedinthefollowingthreesteps: Step1:Computethenormalizedhistogramoftheinputimage. Step2:Computethecumulativedistributionfunction(CDF)ofthehistogram. Step3:Computethebetween-classvarianceforeachpossiblethresholdvaluet,andchoosethethresholdwiththehighestbetween-classvariance. ThealgorithmiccomplexityoftheOtsumethodisO(G),whereGisthenumberofpossiblegraylevelsintheimage.TheOtsumethodiscomputationallyefficientandcanbeeasilyimplementedinsoftware.However,theOtsumethodhassomelimitations,suchasitssensitivitytonoiseandthedifficultyinselectionoftheoptimalthreshold. ImprovedOtsuAlgorithm TheproposedimprovedOtsualgorithmisbasedonthetwo-dimensionalhistogramoftheimage.Thetwo-dimensionalhistogramisconstructedbyusingthegreyvalueandthelocalvarianceofeachpixelintheimage.Thevariancevaluereflectsthenoisele