预览加载中，请您耐心等待几秒...

基于改进BBO算法的二维交叉熵多阈值图像分割（英文）.docx

预览
1/4
2/4
3/4
4/4

在线预览结束，喜欢就下载吧，查找使用更方便

下载提示 文本预览

如果您无法下载资料，请参考说明：

1、部分资料下载需要金币，请确保您的账户上有足够的金币

2、已购买过的文档，再次下载不重复扣费

3、资料包下载后请先用软件解压，在使用对应软件打开

基于改进BBO算法的二维交叉熵多阈值图像分割（英文） Abstract: Themulti-thresholdingimagesegmentationisachallengingtaskinthefieldofimageprocessing.Inthispaper,weproposeanovelapproachformulti-thresholdingimagesegmentationusinganimprovedBiogeography-BasedOptimization(BBO)algorithm.Theproposedalgorithmutilizesthecross-entropymethod(CEM)tofindtheoptimalthresholdvalues,whichensureshighaccuracyinthesegmentationprocess.Theperformanceoftheproposedalgorithmiscomparedwithotherwell-knownimagesegmentationtechniquessuchasOtsu,Kapur,andParticleSwarmOptimization(PSO)methods.Experimentalresultsshowthattheproposedalgorithmoutperformsthesemethodsintermsofsegmentationaccuracy,computationalcomplexity,andconvergencespeed. Introduction: Imagesegmentationisacrucialtaskinthefieldofimageprocessingandcomputervision.Themainobjectiveofimagesegmentationistopartitionanimageintodifferentregionsorclassesbasedontheirfeaturesorproperties.Thisprocessisusedinvariousapplicationssuchasobjectdetection,medicalimageanalysis,remotesensing,andmanymore.Multi-thresholdingimagesegmentationisoneofthecommonlyusedtechniquesforimagesegmentation,whichinvolvesdividinganimageintomultipleregionsbasedondifferentthresholdvalues.Thismethodispopularduetoitssimplicityandeffectivenessinsegmentingimageswithmultipleobjectsordifferentregions. However,thetraditionalmulti-thresholdingtechniquessufferfromseverallimitations,suchastheselectionofappropriatethresholdvalues,computationalcomplexity,andsensitivitytonoise.Therefore,variousoptimizationtechniqueshavebeenproposedtoimprovetheperformanceofmulti-thresholdingimagesegmentation.Inthispaper,weproposeanimprovedBiogeography-BasedOptimization(BBO)algorithmformulti-thresholdingimagesegmentation.TheBBOalgorithmisapopulation-basedoptimizationtechniquethatisinspiredbythebiogeographytheory.Theproposedalgorithmutilizesthecross-entropymethod(CEM)tooptimizethethresholdvaluesforsegmentation. Therestofthepaperisorganizedasfollows.InSection2,weprovideabriefoverviewoftherelatedwork.InSection3,wedescribetheproposedalgorith