预览加载中，请您耐心等待几秒...

基于超像素分割与闪频特征判别的视频火焰检测.docx

预览
1/2
2/2

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

基于超像素分割与闪频特征判别的视频火焰检测 Abstract Firedetectioninvideosisacriticaltaskforensuringthesafetyofpeopleandproperty.Inthispaper,weproposeafiredetectionapproachbasedonsuperpixelsegmentationandflickerfeaturediscrimination.Themethodcombinestheadvantagesofbothspatialandtemporalinformationtoaccuratelyidentifyfireregions.Experimentsconductedonvariousbenchmarkdatasetsdemonstratetheeffectivenessoftheproposedapproachindetectingflamesinvideos. 1.Introduction Fireaccidentscanresultinsignificantdamagetopropertyandendangerthelivesofindividuals.Promptdetectionoffireiscrucialforeffectivelypreventingandcombatingfireaccidents.Traditionalfiredetectionmethodsoftenrelyonstaticimageanalysisorsimplemotiondetectiontechniques,whichmayleadtofalsealarmsorfailtodetectflames.Inrecentyears,withtheadvancementofcomputervisiontechniques,video-basedfiredetectionapproacheshaveemergedasamorereliableandaccuratesolution. 2.RelatedWork Priorresearchhasexploredvariousapproachesforvideo-basedfiredetection.Backgroundsubtraction,opticalflowanalysis,andcolor-basedmethodsarecommonlyusedtechniques.However,thesemethodshavelimitationsinaccuratelydetectingfireduetofactorssuchasnoise,lightingconditions,andcomplexbackgrounds.Toaddressthesechallenges,moreadvancedtechniquesbasedondeeplearning,superpixelsegmentation,andflickerfeatureanalysishavebeenproposed. 3.ProposedApproach Ourproposedapproachforvideo-basedfiredetectionutilizessuperpixelsegmentationandflickerfeaturediscrimination.Superpixelsegmentationhelpsingroupingsimilarpixelstogether,effectivelyreducingthecomputationalcomplexityandenhancingthediscriminativepowerofsubsequentfiredetectionalgorithms.Flickerfeaturediscriminationisbasedontheobservationthatfireflamesexhibitflickeringcharacteristics,whichcanbeexploitedforaccuratefiredetection. 4.SuperpixelSegmentation Superpixelsegmentationisperformedoneachframeofthevideotogrouppixelswithsimilarcolorsandtexturesintolargerregions.Thisreducesthecomplexityofsubsequentprocessingstepsandprovidesamoremeaningfulrepresentationofthevid