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1、基于多特征信息的疲劳驾驶检测系统研究AbstractAsweknow，fatiguedrivinghasbecome"thenumberonekiller"oftrafficsafety，andwiththepopularizationofdriverfatiguewarningsystem,thecontinuousdevelopmentandimprovementoffatiguedrivingdetectionsystemtechnologyisimminent.Toovercomethelimitationsofasinglesensorinfatiguedetection,wei
2、mprovethefatiguedrivingdetectionratethroughcomprehensiveanalysisthesethreefeaturesofthedriver’seyesandmouthstatus,andthevehicletravelingtrajectories.Firstofall,thispaperobtainthedriver'seyes,mouthandtheroadfeaturedatafromthedriver’sfacialimageandroadimagethroughinstallingcamerasinthecarandthefront
3、ofthecar，usingimageacquisitionprogramoftheinfraredlightauxiliarysourcestoensuretheall-timeavailabilityofthesystemandfilterouttheeffectofnaturallight；extractingtheeyefatiguecharacteristicbytextureanalysisinfrareddetectionmethod，andthendetectandlocatetheeyesandmouthareabytheintelligentADABOOSTalgori
4、thm;wefirstlocatethenose,andthenenhancethemouthdetectionratethroughthegeometricpositionrelationshipofnoseandmouse，thencalculatetheopeningdegreeofthemouthaccordingtotheareathesize;calculatinglaneofroadimageusingasimplelinearlanemodel,andobtaintheparametricofthelinearlanemodelusingthebetterrobustnes
5、sprobabilityHoughtransform,socalculatetheyawrate.Thispaperproposetheeyesclosedtimeratetoanalyzeeyefeature,onthebasisofPERCLOSalgorithm,thismethodlettheratioofthedetectedeyesclosedtimeandnormaleyesclosedtimeasthestandardoffatigueanalysis,forthemouthfatigueCharacteristicAnalysis,weusethedual-thresho
6、ldyawnanalysismethodstoanalyzefatigueanddistinguishnon-yawn;thispaperdetectslanedeviationusingtheyawrate,whichisdefinedastheratiooftheleftandrightlanelinesandtheimagehorizontalaxisangle.Finally,dofusionanalysisusingtheweightedaverage,withselectthePRECLOS,theeyesclosedtime,yawntimeandthelaneyawrate
7、asthefeaturesvalue,experimentshowthattheaccuracyratehasgreatlyimproved.Keywords:AutomobileActivesafety;fatiguedrivingdetection;informationfusion;featureextraction;imageacquisition4万方数据西华大学硕士学位论文目录XihuaUniversity.
