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1、JournalofBeijingInstituteofTechnology,2009,Vol.18,No.1ImageRetrievalApproachBasedonIntuitiveFuzzySetCombinedwithGeneticAlgorithm121WANGXiao2yin(王潇茵),XUWei2hua(徐卫华),HUChang2zhen(胡昌振)(1.LabofComputerNetworkDefenseTechnology,BeijingInstituteofTechnology,Beijing10
2、0081,China;2.AutomationStationofArmyAviationDepartmentoftheGeneralStaff,Beijing100012,China)Abstract:Aimingatshortcomingsoftraditionalimageretrievalsystems,anewimageretrievalapproachbasedoncolorfeaturesofimagecombiningintuitivefuzzytheorywithgeneticalgorithmis
3、proposed.Eachimageissegmentedintoaconstantnumberofsub2imagesinverticaldirection.Colorfeaturesareextractedfromeverysub2imagetogetchromosomecoding.Itisconsideredthatfuzzymembershipandintuitivefuzzyhesitancyde2greeofeverypixel’scolorinimageareassociatedtoalltheco
4、lorhistogrambins.Certainfeature,fuzzyfeatureandintuitivefuzzyfeatureofcolorsinanimage,areusedtogethertodescribethecontentofimage.Efficientcombinationsofsub2imageareselectedaccordingtooperationofselecting,crossingandvariation.Retrievalre2sultsareobtainedfromima
5、gematchingbasedonthesecolorfeaturecombinationsofsub2images.Testsshowthatthisapproachcanimprovetheaccuracyofimageretrievalinthecaseofnotdecreasingthespeedofimageretrieval.Itsmeanprecisionisabove80%.Keywords:intuitivefuzzy;geneticalgorithm;colorhistogram;imagere
6、trievalCLCnumber:TP391Documentcode:AArticleID:100420579(2009)0120060205[1]AscomputertechnologyandInternettechnologyrithmstoevaluateimagefeatures.Yangusedthearedevelopingquickly,thereismoreandmoreinfor2algorithmtoestimatecrossoverprobabilityandmuta2mationspread
7、ingontheInternet.Imageisanimpor2tionprobabilitybasedonfuzzyreasoningtechnolo2[2]tantinformationcarrier,andimageretrievaltechnol2gy.Soodamanimodeledfeaturesbyfuzzymember2ogybecomesthefocusofresearch.Themostfounda2shipfunctionsbasedonaprioriknowledge,andin2tiona
8、ltaskofimageretrievalisextractingfeaturescorporatedageneticalgorithm2basedlearning[3]fromimages.Inordertoexpressthecontentofimageparadigminthefeedbackpathofthesystem.Theaccurately,
